Methods for predicting cortical UP and DOWN states from the phase of deep layer local field potentials

Spontaneous slow wave oscillations in extracellular field potential recordings reflect the alternating dominance of excitation and inhibition

In the resting state, cortical neurons can fire action potentials spontaneously but synchronously (Up state), followed by a quiescent period (Down state) before the cycle repeats. Extracellular recordings in the infragranular layer of cortex with a micro-electrode display a negative deflection (depth-negative) during Up states and a positive deflection (depth-positive) during Down states. The resulting slow wave oscillation (SWO) has been studied extensively during sleep and under anaesthesia. However, recent research on the balanced nature of synaptic excitation and inhibition has highlighted our limited understanding of its genesis. Specifically, are excitation and inhibition balanced during SWOs? We analyse spontaneous local field potentials (LFPs) during SWOs recorded from anaesthetised rats via a multi-channel laminar micro-electrode and show that the Down state consists of two distinct synaptic states: a Dynamic Down state associated with depth-positive LFPs and a prominent dipole in the extracellular field, and a Static Down state with negligible (≈ 0 mV $ \approx 0{\mathrm{\;mV}}$ ) LFPs and a lack of dipoles extracellularly. We demonstrate that depth-negative and -positive LFPs are generated by a shift in the balance of synaptic excitation and inhibition from excitation dominance (depth-negative) to inhibition dominance (depth-positive) in the infragranular layer neurons. Thus, although excitation and inhibition co-tune overall, differences in their timing lead to an alternation of dominance, manifesting as SWOs. We further show that Up state initiation is significantly faster if the preceding Down state is dynamic rather than static. Our findings provide a coherent picture of the dependence of SWOs on synaptic activity. KEY POINTS: Cortical neurons can exhibit repeated cycles of spontaneous activity interleaved with periods of relative silence, a phenomenon known as 'slow wave oscillation' (SWO). During SWOs, recordings of local field potentials (LFPs) in the neocortex show depth-negative deflection during the active period (Up state) and depth-positive deflection during the silent period (Down state). Here we further classified the Down state into a dynamic phase and a static phase based on a novel method of classification and revealed non-random, stereotypical sequences of the three states occurring with significantly different transitional kinetics. Our results suggest that the positive and negative deflections in the LFP reflect the shift of the instantaneous balance between excitatory and inhibitory synaptic activity of the local cortical neurons. The differences in transitional kinetics may imply distinct synaptic mechanisms for Up state initiation. The study may provide a new approach for investigating spontaneous brain rhythms.

Temporal disparity of action potentials triggered in axon initial segments and distal axons in the neocortex

Neural population activity determines the timing of synaptic inputs, which arrive to dendrites, cell bodies, and axon initial segments (AISs) of cortical neurons. Action potential initiation in the AIS (AIS-APs) is driven by input integration, and the phase preference of AIS-APs during network oscillations is characteristic to cell classes. Distal regions of cortical axons do not receive synaptic inputs, yet experimental induction protocols can trigger retroaxonal action potentials (RA-APs) in axons distal from the soma. We report spontaneously occurring RA-APs in human and rodent cortical interneurons that appear uncorrelated to inputs and population activity. Network-linked triggering of AIS-APs versus input-independent timing of RA-APs of the same interneurons results in disparate temporal contribution of a single cell to in vivo network operation through perisomatic and distal axonal firing.

Hippocampal memory reactivation during sleep is correlated with specific cortical states of the retrosplenial and prefrontal cortices

Episodic memories are thought to be stabilized through the coordination of cortico-hippocampal activity during sleep. However, the timing and mechanism of this coordination remain unknown. To investigate this, we studied the relationship between hippocampal reactivation and slow-wave sleep up and down states of the retrosplenial cortex (RTC) and prefrontal cortex (PFC). We found that hippocampal reactivations are strongly correlated with specific cortical states. Reactivation occurred during sustained cortical Up states or during the transition from up to down state. Interestingly, the most prevalent interaction with memory reactivation in the hippocampus occurred during sustained up states of the PFC and RTC, while hippocampal reactivation and cortical up-to-down state transition in the RTC showed the strongest coordination. Reactivation usually occurred within 150-200 msec of a cortical Up state onset, indicating that a buildup of excitation during cortical Up state activity influences the probability of memory reactivation in CA1. Conversely, CA1 reactivation occurred 30-50 msec before the onset of a cortical down state, suggesting that memory reactivation affects down state initiation in the RTC and PFC, but the effect in the RTC was more robust. Our findings provide evidence that supports and highlights the complexity of bidirectional communication between cortical regions and the hippocampus during sleep.

A brain cytokine-independent switch in cortical activity marks the onset of sickness behavior triggered by acute peripheral inflammation

Systemic inflammation triggers protective as well as pro-inflammatory responses in the brain based on neuronal and/or cytokine signaling, and it associates with acutely and protractedly disrupted cognition. However, the multiple mechanisms underlying the peripheral-central inflammatory signaling are still not fully characterized. We used intraperitoneal (i.p.) injection of lipopolysaccharide (LPS) in freely moving mice with chronically implanted electrodes for recording of local field potentials (LFP) and electrocorticography (ECoG) in the hippocampus and neocortex, respectively. We show here that a sudden switch in the mode of network activity occurred in both areas starting at 10-15 min after the LPS injection, simultaneously with a robust change from exploration to sickness behavior. This switch in cortical mode commenced before any elevations in pro-inflammatory cytokines IL-1β, TNFα, CCL2 or IL-6 were detected in brain tissue. Thereafter, this mode dominated cortical activity for the recording period of 3 h, except for a partial and transient recovery around 40 min post-LPS. These effects were closely paralleled by changes in ECoG spectral entropy. Continuous recordings for up to 72 h showed a protracted attenuation in hippocampal activity, while neocortical activity recovered after 48 h. The acute sickness behavior recovered by 72 h post-LPS. Notably, urethane (1.3 mg/kg) administered prior to LPS blocked the early effect of LPS on cortical activity. However, experiments under urethane anesthesia which were started 24 h post-LPS (with neuroinflammation fully developed before application of urethane) showed that both theta-supratheta and fast gamma CA1 activity were reduced, DG delta activity was increased, and sharp-wave ripples were abolished. Finally, we observed that experimental compensation of inflammation-induced hypothermia 24-48 h post-LPS promoted seizures and status epilepticus; and that LPS decreased the threshold of kainate-provoked seizures beyond the duration of acute sickness behavior indicating post-acute inflammatory hyperexcitability. Taken together, the strikingly fast development and initial independence of brain cytokines of the LPS-induced cortical mode, its spectral characteristics and simultaneity in hippocampus and neocortex, as well as inhibition by pre-applied urethane, strongly suggest that the underlying mechanisms are based on activation of the afferent vagus nerve and its mainly cholinergic ascending projections to higher brain areas.

Ketamine affects homeostatic sleep regulation in the absence of the circadian sleep-regulating component in freely moving rats

Pharmacological effects of ketamine may affect homeostatic sleep regulation via slow wave related mechanisms. In the present study effects of ketamine applied at anesthetic dose (80 mg/kg) were tested on neocortical electric activity for 24 h in freely moving rats. Ketamine effects were compared to changes during control (saline) injections and after 6 h gentle handling sleep deprivation (SD). As circadian factors may mask drug effects, an illumination protocol consisting of short light-dark cycles was applied. Ketamine application induced a short hypnotic stage with characteristic slow cortical rhythm followed by a long-lasting hyperactive waking resulting pharmacological SD. Coherence analysis indicated an increased level of local synchronization in broad local field potential frequency ranges during hyperactive waking but not during natural- or SD-evoked waking. Both slow wave sleep and rapid eye movement sleep were replaced after the termination of the ketamine effect. Our results show that both ketamine-induced hypnotic state and hyperactive waking can induce homeostatic sleep pressure with comparable intensity as 6 h SD, but ketamine-induced waking was different compared to the SD-evoked one. Both types of waking stages were different compared to spontaneous waking but all three types of wakefulness can engage the homeostatic sleep regulating machinery to generate sleep pressure dissipated by subsequent sleep. Current-source density analysis of the slow waves showed that cortical transmembrane currents were stronger during ketamine-induced hypnotic stage compared to both sleep replacement after SD and ketamine application, but intracortical activation patterns showed only quantitative differences. These findings may hold some translational value for human medical ketamine applications aiming the treatment of depression-associated sleep problems, which can be alleviated by the homeostatic sleep effect of the drug without the need for an intact circadian regulation.

Stimulus Feature-Specific Control of Layer 2/3 Subthreshold Whisker Responses by Layer 4 in the Mouse Primary Somatosensory Cortex

In the barrel field of the rodent primary somatosensory cortex (S1bf), excitatory cells in layer 2/3 (L2/3) display sparse firing but reliable subthreshold response during whisker stimulation. Subthreshold responses encode specific features of the sensory stimulus, for example, the direction of whisker deflection. According to the canonical model for the flow of sensory information across cortical layers, activity in L2/3 is driven by layer 4 (L4). However, L2/3 cells receive excitatory inputs from other regions, raising the possibility that L4 partially drives L2/3 during whisker stimulation. To test this hypothesis, we combined patch-clamp recordings from L2/3 pyramidal neurons in S1bf with selective optogenetic inhibition of L4 during passive whisker stimulation in both anesthetized and awake head-restrained mice. We found that L4 optogenetic inhibition did not abolish the subthreshold whisker-evoked response nor it affected spontaneous membrane potential fluctuations of L2/3 neurons. However, L4 optogenetic inhibition decreased L2/3 subthreshold responses to whisker deflections in the preferred direction, and it increased L2/3 responses to stimuli in the nonpreferred direction, leading to a change in the direction tuning. Our results contribute to reveal the circuit mechanisms underlying the processing of sensory information in the rodent S1bf.

Thalamus mediates neocortical Down state transition via GABAB-receptor-targeting interneurons

Slow-wave sleep is characterized by near-synchronous alternation of active Up states and quiescent Down states in the neocortex. Although the cortex itself can maintain these oscillations, the full expression of Up-Down states requires intact thalamocortical circuits. Sensory thalamic input can drive the cortex into an Up state. Here we show that midline thalamic neurons terminate Up states synchronously across cortical areas. Combining local field potential, single-unit, and patch-clamp recordings in conjunction with optogenetic stimulation and silencing in mice in vivo, we report that thalamic input mediates Down transition via activation of layer 1 neurogliaform inhibitory neurons acting on GABA_B receptors. These results strengthen the evidence that thalamocortical interactions are essential for the full expression of slow-wave sleep, show that Down transition is an active process mediated by cortical GABA_B receptors, and demonstrate that thalamus synchronizes Down transitions across cortical areas during natural slow-wave sleep.

Modulation of Prefrontal Cortex Slow Oscillations by Phasic Activation of the Locus Coeruleus

Cortical slow rhythmic activity, a hallmark of deep sleep, is observed under urethane anesthesia. Synchronized fluctuations of the membrane excitability of a large neuronal population are reflected in the extracellular Local Field Potential (LFP), as high-amplitude slow (∼1 Hz) oscillations (SO). The SO-phase indicates the presence (Up) or absence (Down) of neuronal spiking. The cortical state is controlled by the input from thalamic and neuromodulatory centers, including the brainstem noradrenergic nucleus Locus Coeruleus (LC). The bidirectional modulation of neuronal excitability by noradrenaline (NA) is well known. We have previously shown that LC phasic activation caused transient excitability increase in the medial prefrontal cortex (mPFC). In the present study, we characterized the effect of LC phasic activation on the prefrontal population dynamics at a temporal scale of a single SO cycle. We applied short (0.2 s) trains of electric pulses (0.02-0.05 mA at 20-50 Hz) to the LC cell bodies and monitored a broadband (0.1 Hz-8 kHz) mPFC LFP in urethane-anesthetized rats. The direct electrical stimulation of LC (LC-DES), applied during the Up-phase, enhanced the firing probability in the mPFC by ∼20% and substantially prolonged Up-states in 56% of trials. The LC-DES applied during Down-phase caused a rapid Down-to-Up transition in 81.5% of trials. The LC-DES was more effective at a higher frequency, but not at a higher current. Our results suggest that transient NA release, coupled to SO, may promote synaptic plasticity and memory consolidation by sustaining a depolarized state in the mPFC neurons.

Network Asynchrony Underlying Increased Broadband Gamma Power

Synchronous activity of cortical inhibitory interneurons expressing parvalbumin (PV) underlies expression of cortical γ rhythms. Paradoxically, deficient PV inhibition is associated with increased broadband γ power in the local field potential. Increased baseline broadband γ is also a prominent characteristic in schizophrenia and a hallmark of network alterations induced by NMDAR antagonists, such as ketamine. Whether enhanced broadband γ is a true rhythm, and if so, whether rhythmic PV inhibition is involved or not, is debated. Asynchronous and increased firing activities are thought to contribute to broadband power increases spanning the γ band. Using male and female mice lacking NMDAR activity specifically in PV neurons to model deficient PV inhibition, we here show that neuronal activity with decreased synchronicity is associated with increased prefrontal broadband γ power. Specifically, reduced spike time precision and spectral leakage of spiking activity because of higher firing rates (spike "contamination") affect the broadband γ band. Desynchronization was evident at multiple time scales, with reduced spike entrainment to the local field potential, reduced cross-frequency coupling, and fragmentation of brain states. Local application of S(+)-ketamine in (control) mice with intact NMDAR activity in PV neurons triggered network desynchronization and enhanced broadband γ power. However, our investigations suggest that disparate mechanisms underlie increased broadband γ power caused by genetic alteration of PV interneurons and ketamine-induced power increases in broadband γ. Our study confirms that enhanced broadband γ power can arise from asynchronous activities and demonstrates that long-term deficiency of PV inhibition can be a contributor.SIGNIFICANCE STATEMENT Brain oscillations are fundamental to the coordination of neuronal activity across neurons and structures. γ oscillations (30-80 Hz) have received particular attention through their association with perceptual and cognitive processes. Synchronous activity of inhibitory parvalbumin (PV) interneurons generates cortical γ oscillation, but, paradoxically, PV neuron deficiency is associated with increases in γ oscillations. We here reconcile this conundrum and show how deficient PV inhibition can lead to increased and asynchronous excitatory firing, contaminating the local field potential and manifesting as increased γ power. Thus, increased γ power does not always reflect a genuine rhythm. Further, we show that ketamine-induced γ increases are caused by separate network mechanisms.

Cholinergic modulation of Up-Down states in the mouse medial entorhinal cortex in vitro

Cholinergic tone is high during wake and rapid eye movement sleep and lower during slow wave sleep (SWS). Nevertheless, the low tone of acetylcholine during SWS modulates sharp wave ripple incidence in the hippocampus and slow wave activity in the neocortex. Linking the hippocampus and neocortex, the medial entorhinal cortex (mEC) regulates the coupling between these structures during SWS, alternating between silent Down states and active Up states, which outlast neocortical ones. Here, we investigated how low physiological concentrations of acetylcholine (ACh; 100-500 nM) modulate Up and Down states in a mEC slice preparation. We find that ACh has a dual effect on mEC activity: it prolongs apparent Up state duration as recorded in individual cells and decreases the total synaptic charge transfer, without affecting the duration of detectable synaptic activity. The overall outcome of ACh application is excitatory and we show that ACh increases Up state incidence via muscarinic receptor activation. The mean firing rate of principal neurons increased in around half of the cells while the other half showed a decrease in firing rate. Using two-photon calcium imaging of population activity, we found that population-wide network events are more frequent and rhythmic during ACh and confirmed that ACh modulates cell participation in these network events, consistent with a role for cholinergic modulation in regulating information flow between the hippocampus and neocortex during SWS.

Region-specific adenosinergic modulation of the slow-cortical rhythm in urethane-anesthetized rats

Slow cortical rhythm (SCR) is a rhythmic alternation of UP and DOWN states during sleep and anesthesia. SCR-associated slow waves reflect homeostatic sleep functions. Adenosine accumulating during prolonged wakefulness and sleep deprivation (SD) may play a role in the delta power increment during recovery sleep. NREM sleep is a local, use-dependent process of the brain. In the present study, direct effect of adenosine on UP and DOWN states was tested by topical application to frontal, somatosensory and visual cortices, respectively, in urethane-anesthetized rats. Local field potentials (LFPs) were recorded using an electrode array inserted close to the location of adenosine application. Multiple unit activity (MUA) was measured from layer V-VI in close proximity of the recording array. In the frontal and somatosensory cortex, adenosine modulated SCR with slow kinetics on the LFP level while MUA remained mostly unaffected. In the visual cortex, adenosine modulated SCR with fast kinetics. In each region, delta power increment was based on the increased frequency of state transitions as well as increased height of UP-state associated slow waves. These results show that adenosine may directly modulate SCR in a complex and region-specific manner which may be related to the finding that restorative processes may take place with varying duration and intensity during recovery sleep in different cortical regions. Adenosine may play a direct role in the increment of the slow wave power observed during local sleep, furthermore it may shape the region-specific characteristics of the phenomenon.

LFP clustering in cortex reveals a taxonomy of Up states and near-millisecond, ordered phase-locking in cortical neurons

During slow-wave sleep and anesthesia, mammalian cortex exhibits a synchronized state during which neurons shift from a largely nonfiring to a firing state, known as an Up-state transition. Up-state transitions may constitute the default activity pattern of the entire cortex (Neske GT. Front Neural Circuits 9: 88, 2016) and could be critical to understanding cortical function, yet the genesis of such transitions and their interaction with single neurons is not well understood. It was recently shown that neurons firing at rates >2 Hz fire spikes in a stereotyped order during Up-state transitions (Luczak A, McNaughton BL, Harris KD. Nat Rev Neurosci 16: 745-755, 2015), yet it is still unknown if Up states are homogeneous and whether spiking order is present in neurons with rates <2 Hz (the majority). Using extracellular recordings from anesthetized cats and mice and from naturally sleeping rats, we show for the first time that Up-state transitions can be classified into several types based on the shape of the local field potential (LFP) during each transition. Individual LFP events could be localized in time to within 1-4 ms, more than an order of magnitude less than in previous studies. The majority of recorded neurons synchronized their firing to within ±5-15 ms relative to each Up-state transition. Simultaneous electrophysiology and wide-field imaging in mouse confirmed that LFP event clusters are cortex-wide phenomena. Our findings show that Up states are of different types and point to the potential importance of temporal order and millisecond-scale signaling by cortical neurons.NEW & NOTEWORTHY During cortical Up-state transitions in sleep and anesthesia, neurons undergo brief periods of increased firing in an order similar to that occurring in awake states. We show that these transitions can be classified into distinct types based on the shape of the local field potential. Transition times can be defined to <5 ms. Most neurons synchronize their firing to within ±5-15 ms of the transitions and fire in a consistent order.

Functional determinants of enhanced and depressed interareal information flow in nonrapid eye movement sleep between neuronal ensembles in rat cortex and hippocampus

Compared with wakefulness, neuronal activity during nonrapid eye movement (NREM) sleep is characterized by a decreased ability to integrate information, but also by the reemergence of task-related information patterns. To investigate the mechanisms underlying these seemingly opposing phenomena, we measured directed information flow by computing transfer entropy between neuronal spiking activity in three cortical regions and the hippocampus of rats across brain states. State-dependent information flow was jointly determined by the anatomical distance between neurons and by their functional specialization. We distinguished two regimes, operating at short and long time scales, respectively. From wakefulness to NREM sleep, transfer entropy at short time scales increased for interareal connections between neurons showing behavioral task correlates. Conversely, transfer entropy at long time scales became stronger between nontask modulated neurons and weaker between task-modulated neurons. These results may explain how, during NREM sleep, a global interareal disconnection is compatible with highly specific task-related information transfer.

Tone frequency representation beyond the tonotopic map: Cross-correlation between ongoing activity in the rat auditory cortex

Functional maps play crucial roles in the neural representations of the sensory cortices, although such representations occasionally extend beyond these maps. For example, the auditory cortex exhibits distinct tonotopic activation at the onset of tone, which is followed by rapid decays in the majority of neuronal signals and ongoing activities in only a small number of neurons. Such ongoing activity should be maintained by the cortical states. To better understand maintenance of ongoing activity beyond that triggered directly by stimuli, we used a rat model. Here, we hypothesized that neural correlations between local field potentials (LFPs) within a local area of the auditory cortex may serve as a measure of the cortical state underlying ongoing activity. We densely mapped the auditory cortex of rats and demonstrated that cross-correlation patterns of ongoing activity were highly decodable. Informative features were widely distributed over the auditory cortex and across multiple frequency bands. Furthermore, acoustic trauma disrupted tonotopic representation at the onset but did not affect neural representations by the correlation of ongoing activities. These results suggest that cross-correlations of LFP within the auditory cortex represent frequencies of sustained auditory stimuli, and that these representations are made beyond direct tonotopic activation at stimulus onset.

Thalamic Drive of Cortical Parvalbumin-Positive Interneurons during Down States in Anesthetized Mice

Up and down states are among the most prominent features of the thalamo-cortical system during non-rapid eye movement (NREM) sleep and many forms of anesthesia. Cortical interneurons, including parvalbumin (PV) cells, display firing activity during cortical down states, and this GABAergic signaling is associated with prolonged down-state durations. However, what drives PV interneurons to fire during down states remains unclear. We here tested the hypothesis that background thalamic activity may lead to suprathreshold activation of PV cells during down states. To this aim, we performed two-photon guided juxtasomal recordings from PV interneurons in the barrel field of the somatosensory cortex (S1bf) of anesthetized mice, while simultaneously collecting the local field potential (LFP) in S1bf and the multi-unit activity (MUA) in the ventral posteromedial (VPM) thalamic nucleus. We found that activity in the VPM was associated with longer down-state duration in S1bf and that down states displaying PV cell firing were associated with increased VPM activity. Moreover, thalamic inhibition through application of muscimol reduced the fraction of spikes discharged by PV cells during cortical down states. Finally, we inhibited PV interneurons using optogenetics during down states while monitoring cortical LFP under control conditions and after thalamic muscimol injection. We found increased latency of the optogenetically triggered down-to-up transitions upon thalamic pharmacological blockade compared to controls. These findings demonstrate that spontaneous thalamic activity inhibits cortex during down states through the activation of PV interneurons.

Fine-scale mapping of cortical laminar activity during sleep slow oscillations using high-density linear silicon probes

BACKGROUND

The cortical slow (∼1 Hz) oscillation (SO), which is thought to play an active role in the consolidation of memories, is a brain rhythm characteristic of slow-wave sleep, with alternating periods of neuronal activity and silence. Although the laminar distribution of cortical activity during SO is well-studied by using linear neural probes, traditional devices have a relatively low (20-100 μm) spatial resolution along cortical layers.

NEW METHOD

In this work, we demonstrate a high-density linear silicon probe fabricated to record the SO with very high spatial resolution (∼6 μm), simultaneously from multiple cortical layers. Ketamine/xylazine-induced SO was acquired acutely from the neocortex of rats, followed by the examination of the high-resolution laminar structure of cortical activity.

RESULTS

The probe provided high-quality extracellular recordings, and the obtained cortical laminar profiles of the SO were in good agreement with the literature data. Furthermore, we could record the simultaneous activity of 30-50 cortical single units. Spiking activity of these neurons showed layer-specific differences.

COMPARISON WITH EXISTING METHODS

The developed silicon probe measures neuronal activity with at least a three-fold higher spatial resolution compared with traditional linear probes. By exploiting this feature, we could determine the site of up-state initiation with a higher precision than before. Additionally, increased spatial resolution may provide more reliable spike sorting results, as well as a higher single unit yield.

CONCLUSIONS

The high spatial resolution provided by the electrodes allows to examine the fine structure of local population activity during sleep SO in greater detail.

Sleep- and Wake-Like States in Small Networks In Vivo and In Vitro

Wakefulness and sleep are highly complex and heterogeneous processes, involving multiple neurotransmitter systems and a sophisticated interplay between global and local networks of neurons and non-neuronal cells. Macroscopic approaches applied at the level of the whole organism, view sleep as a global behaviour and allow for investigation into aspects such as the effects of insufficient or disrupted sleep on cognitive function, metabolism, thermoregulation and sensory processing. While significant progress has been achieved using such large-scale approaches, the inherent complexity of sleep-wake regulation has necessitated the development of methods which tackle specific aspects of sleep in isolation. One way this may be achieved is by investigating specific cellular or molecular phenomena in the whole organism in situ, either during spontaneous or induced sleep-wake states. This approach has greatly advanced our knowledge about the electrophysiology and pharmacology of ion channels, specific receptors, intracellular pathways and the small networks implicated in the control and regulation of the sleep-wake cycle. Importantly though, there are a variety of external and internal factors that influence global behavioural states which are difficult to control for using these approaches. For this reason, over the last few decades, ex vivo experimental models have become increasingly popular and have greatly advanced our understanding of many fundamental aspects of sleep, including the neuroanatomy and neurochemistry of sleep states, sleep regulation, the origin and dynamics of specific sleep oscillations, network homeostasis as well as the functional roles of sleep. This chapter will focus on the use of small neuronal networks as experimental models and will highlight the most significant and novel insights these approaches have provided.

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.

Spike-Based Functional Connectivity in Cerebral Cortex and Hippocampus: Loss of Global Connectivity Is Coupled to Preservation of Local Connectivity During Non-REM Sleep

Behavioral states are commonly considered global phenomena with homogeneous neural determinants. However, recent studies indicate that behavioral states modulate spiking activity with neuron-level specificity as a function of brain area, neuronal subtype, and preceding history. Although functional connectivity also strongly depends on behavioral state at a mesoscopic level and is globally weaker in non-REM (NREM) sleep and anesthesia than wakefulness, it is unknown how neuronal communication is modulated at the cellular level. We hypothesize that, as for neuronal activity, the influence of behavioral states on neuronal coupling strongly depends on type, location, and preceding history of involved neurons. Here, we applied nonlinear, information-theoretical measures of functional connectivity to ensemble recordings with single-cell resolution to quantify neuronal communication in the neocortex and hippocampus of rats during wakefulness and sleep. Although functional connectivity (measured in terms of coordination between firing rate fluctuations) was globally stronger in wakefulness than in NREM sleep (with distinct traits for cortical and hippocampal areas), the drop observed during NREM sleep was mainly determined by a loss of inter-areal connectivity between excitatory neurons. Conversely, local (intra-area) connectivity and long-range (inter-areal) coupling between interneurons were preserved during NREM sleep. Furthermore, neuronal networks that were either modulated or not by a behavioral task remained segregated during quiet wakefulness and NREM sleep. These results show that the drop in functional connectivity during wake-sleep transitions globally holds true at the cellular level, but confine this change mainly to long-range coupling between excitatory neurons.

SIGNIFICANCE STATEMENT

Studies performed at a mesoscopic level of analysis have shown that communication between cortical areas is disrupted in non-REM sleep and anesthesia. However, the neuronal determinants of this phenomenon are not known. Here, we applied nonlinear, information-theoretical measures of functional coupling to multi-area tetrode recordings from freely moving rats to investigate whether and how brain state modulates coordination between individual neurons. We found that the previously observed drop in functional connectivity during non-REM (NREM) sleep can be explained by a decrease in coupling between excitatory neurons located in distinct brain areas. Conversely, intra-area communication and coupling between interneurons are preserved. Our results provide significant new insights into the neuron-level mechanisms responsible for the loss of consciousness occurring in NREM sleep.

An inhibitory gate for state transition in cortex

Large scale transitions between active (up) and silent (down) states during quiet wakefulness or NREM sleep regulate fundamental cortical functions and are known to involve both excitatory and inhibitory cells. However, if and how inhibition regulates these activity transitions is unclear. Using fluorescence-targeted electrophysiological recording and cell-specific optogenetic manipulation in both anesthetized and non-anesthetized mice, we found that two major classes of interneurons, the parvalbumin and the somatostatin positive cells, tightly control both up-to-down and down-to-up state transitions. Inhibitory regulation of state transition was observed under both natural and optogenetically-evoked conditions. Moreover, perturbative optogenetic experiments revealed that the inhibitory control of state transition was interneuron-type specific. Finally, local manipulation of small ensembles of interneurons affected cortical populations millimetres away from the modulated region. Together, these results demonstrate that inhibition potently gates transitions between cortical activity states, and reveal the cellular mechanisms by which local inhibitory microcircuits regulate state transitions at the mesoscale.

DOI:http://dx.doi.org/10.7554/eLife.26177.001

Phase analysis method for burst onset prediction

The response of bursting neurons to fluctuating inputs is usually hard to predict, due to their strong nonlinearity. For the same reason, decoding the injected stimulus from the activity of a bursting neuron is generally difficult. In this paper we propose a method describing (for neuron models) a mechanism of phase coding relating the burst onsets with the phase profile of the input current. This relation suggests that burst onset may provide a way for postsynaptic neurons to track the input phase. Moreover, we define a method of phase decoding to solve the inverse problem and estimate the likelihood of burst onset given the input state. Both methods are presented here in a unified framework, describing a complete coding-decoding procedure. This procedure is tested by using different neuron models, stimulated with different inputs (stochastic, sinusoidal, up, and down states). The results obtained show the efficacy and broad range of application of the proposed methods. Possible applications range from the study of sensory information processing, in which phase-of-firing codes are known to play a crucial role, to clinical applications such as deep brain stimulation, helping to design stimuli in order to trigger or prevent neural bursting.

Models of Neuronal Stimulus-Response Functions: Elaboration, Estimation, and Evaluation

Rich, dynamic, and dense sensory stimuli are encoded within the nervous system by the time-varying activity of many individual neurons. A fundamental approach to understanding the nature of the encoded representation is to characterize the function that relates the moment-by-moment firing of a neuron to the recent history of a complex sensory input. This review provides a unifying and critical survey of the techniques that have been brought to bear on this effort thus far—ranging from the classical linear receptive field model to modern approaches incorporating normalization and other nonlinearities. We address separately the structure of the models; the criteria and algorithms used to identify the model parameters; and the role of regularizing terms or “priors.” In each case we consider benefits or drawbacks of various proposals, providing examples for when these methods work and when they may fail. Emphasis is placed on key concepts rather than mathematical details, so as to make the discussion accessible to readers from outside the field. Finally, we review ways in which the agreement between an assumed model and the neuron's response may be quantified. Re-implemented and unified code for many of the methods are made freely available.

Large-scale recording of thalamocortical circuits: in vivo electrophysiology with the two-dimensional electronic depth control silicon probe

Recording simultaneous activity of a large number of neurons in distributed neuronal networks is crucial to understand higher order brain functions. We demonstrate the in vivo performance of a recently developed electrophysiological recording system comprising a two-dimensional, multi-shank, high-density silicon probe with integrated complementary metal-oxide semiconductor electronics. The system implements the concept of electronic depth control (EDC), which enables the electronic selection of a limited number of recording sites on each of the probe shafts. This innovative feature of the system permits simultaneous recording of local field potentials (LFP) and single- and multiple-unit activity (SUA and MUA, respectively) from multiple brain sites with high quality and without the actual physical movement of the probe. To evaluate the in vivo recording capabilities of the EDC probe, we recorded LFP, MUA, and SUA in acute experiments from cortical and thalamic brain areas of anesthetized rats and mice. The advantages of large-scale recording with the EDC probe are illustrated by investigating the spatiotemporal dynamics of pharmacologically induced thalamocortical slow-wave activity in rats and by the two-dimensional tonotopic mapping of the auditory thalamus. In mice, spatial distribution of thalamic responses to optogenetic stimulation of the neocortex was examined. Utilizing the benefits of the EDC system may result in a higher yield of useful data from a single experiment compared with traditional passive multielectrode arrays, and thus in the reduction of animals needed for a research study.

Propagation of spontaneous slow-wave activity across columns and layers of the adult rat barrel cortex in vivo

During slow-wave sleep, neocortical networks exhibit self-organized activity switching between periods of concurrent spiking (up-states) and periods of network silence (down-states), a phenomenon also occurring under the effects of different anesthetics and in in vitro brain slice preparations. Although this type of ongoing activity has been implicated into important functions such as memory consolidation and learning, the manner in which it propagates across different cortical modules (i.e., columns and layers) has not been fully characterized. In the present study, we investigated this issue by measuring spontaneous activity at large scale in the adult rat barrel cortex under urethane anesthesia by means of voltage-sensitive dye imaging and 128-channel probe recordings. Up to 74 neurons located in all layers of up to four functionally identified barrel-related columns were recorded simultaneously. The spontaneous activity propagated isotropically across the cortical surface with a median speed of ~35 µm/ms. A concomitant radial spread of activation was present from deep to superficial cortical layers. Thus, spontaneous activity occurred rather globally in the barrel cortex, with ≥50 % of the up-states presenting spikes in ≥3 columns and layers. Temporally precise spike sequences, which occurred repeatedly (although sporadically) within the up-states, were typically led by putative excitatory neurons in the infragranular cortical layers. In summary, our data provide for the first time an overall view of the spontaneous slow-wave activity within the barrel cortex circuit, characterizing its propagation across columns and layers at high spatio-temporal resolution.

Quantification of mid and late evoked sinks in laminar current source density profiles of columns in the primary auditory cortex

Current source density (CSD) analysis assesses spatiotemporal synaptic activations at somatic and/or dendritic levels in the form of depolarizing current sinks. Whereas many studies have focused on the short (<50 ms) latency sinks, associated with thalamocortical projections, sinks with longer latencies have received less attention. Here, we analyzed laminar CSD patterns for the first 600 ms after stimulus onset in the primary auditory cortex of Mongolian gerbils. By applying an algorithm for contour calculation, three distinct mid and four late evoked sinks were identified in layers I, III, Va, VIa, and VIb. Our results further showed that the patterns of intracortical information-flow remained qualitatively similar for low and for high sound pressure level stimuli at the characteristic frequency (CF) as well as for stimuli ± 1 octave from CF. There were, however, differences associated with the strength, vertical extent, onset latency, and duration of the sinks for the four stimulation paradigms used. Stimuli one octave above the most sensitive frequency evoked a new, and quite reliable, sink in layer Va whereas low level stimulation led to the disappearance of the layer VIb sink. These data indicate the presence of input sources specifically activated in response to level and/or frequency parameters. Furthermore, spectral integration above vs. below the CF of neurons is asymmetric as illustrated by CSD profiles. These results are important because synaptic feedback associated with mid and late sinks—beginning at 50 ms post stimulus latency—is likely crucial for response modulation resulting from higher order processes like memory, learning or cognitive control.

Cortical state determines global variability and correlations in visual cortex

The response of neurons in sensory cortex to repeated stimulus presentations is highly variable. To investigate the nature of this variability, we compared the spike activity of neurons in the primary visual cortex (V1) of cats with that of their afferents from lateral geniculate nucleus (LGN), in response to similar stimuli. We found variability to be much higher in V1 than in LGN. To investigate the sources of the additional variability, we measured the spiking activity of large V1 populations and found that much of the variability was shared across neurons: the variable portion of the responses of one neuron could be well predicted from the summed activity of the rest of the neurons. Variability thus mostly reflected global fluctuations affecting all neurons. The size and prevalence of these fluctuations, both in responses to stimuli and in ongoing activity, depended on cortical state, being larger in synchronized states than in more desynchronized states. Contrary to previous reports, these fluctuations invested the overall population, regardless of preferred orientation. The global fluctuations substantially increased variability in single neurons and correlations among pairs of neurons. Once this effect was removed, pairwise correlations were reduced and were similar regardless of cortical state. These results highlight the importance of cortical state in controlling cortical operation and can help reconcile previous studies, which differed widely in their estimate of neuronal variability and pairwise correlations.

Disruption of medial prefrontal synchrony in the subchronic phencyclidine model of schizophrenia in rats

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Subchronic PCP pretreatment reduced theta oscillations in medial prefrontal cortex.

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Subchronic PCP pretreatment produced abnormal cortical synchronization in putative cortical pyramidal cells.

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Subchronic PCP pretreatment produced abnormal locking of cortical spikes to lower oscillation frequencies.

Subchronic treatment with the N-methyl-d-aspartate (NMDA) antagonist phencyclidine (PCP) produces behavioral abnormalities in rodents which are considered a reliable pharmacological model of neurocognitive deficits in schizophrenia. Alterations in prefrontal neuronal firing after acute PCP administration have been observed, however enduring changes in prefrontal activity after subchronic PCP treatment have not been studied. To address this we have recorded cortical oscillations and unit responses in putative cortical pyramidal cells in subchronic PCP-treated rats (2 mg/kg twice daily for 7 days) under urethane anesthesia. We found that this regimen reduced theta oscillations in the medial prefrontal cortex. It further produced abnormal cortical synchronization in putative cortical pyramidal cells. These alterations in prefrontal cortex functioning may contribute to cognitive deficits seen in subchronic NMDA antagonist pre-treated animals in prefrontal-dependent tasks.

Amyloid-β disrupts ongoing spontaneous activity in sensory cortex

The effect of Alzheimer's disease pathology on activity of individual neocortical neurons in the intact neural network remains obscure. Ongoing spontaneous activity, which constitutes most of neocortical activity, is the background template on which further evoked-activity is superimposed. We compared in vivo intracellular recordings and local field potentials (LFP) of ongoing activity in the barrel cortex of APP/PS1 transgenic mice and age-matched littermate CONTROLS, following significant amyloid-β (Aβ) accumulation and aggregation. We found that membrane potential dynamics of neurons in Aβ-burdened cortex significantly differed from those of nontransgenic

CONTROLS

durations of the depolarized state were considerably shorter, and transitions to that state frequently failed. The spiking properties of APP/PS1 neurons showed alterations from those of

CONTROLS

both firing patterns and spike shape were changed in the APP/PS1 group. At the population level, LFP recordings indicated reduced coherence within neuronal assemblies of APP/PS1 mice. In addition to the physiological effects, we show that morphology of neurites within the barrel cortex of the APP/PS1 model is altered compared to CONTROLS. These results are consistent with a process where the effect of Aβ on spontaneous activity of individual neurons amplifies into a network effect, reducing network integrity and leading to a wide cortical dysfunction.

Sensory-evoked synaptic integration in cerebellar and cerebral cortical neurons

Neurons integrate synaptic inputs across time and space, a process that determines the transformation of input signals into action potential output. This article explores how synaptic integration contributes to the richness of sensory signalling in the cerebellar and cerebral cortices. Whether a neuron receives a few or a few thousand discrete inputs, most evoked synaptic activity generates only subthreshold membrane potential fluctuations. Sensory tuning of synaptic inputs is typically broad, but short-term dynamics and the interplay between excitation and inhibition restrict action potential firing to narrow windows of opportunity. We highlight the challenges and limitations of the use of somatic recordings in the study of synaptic integration and the importance of active dendritic mechanisms in sensory processing.

Convergence of cortical and thalamic input to direct and indirect pathway medium spiny neurons in the striatum

The major afferent innervation of the basal ganglia is derived from the cortex and the thalamus. These excitatory inputs mainly target the striatum where they innervate the principal type of striatal neuron, the medium-sized spiny neurons (MSNs), and are critical in the expression of basal ganglia function. The aim of this work was to test directly whether corticostriatal and thalamostriatal terminals make convergent synaptic contact with individual direct and indirect pathway MSNs. Individual MSNs were recorded in vivo and labelled by the juxtacellular method in the striatum of BAC transgenic mice in which green fluorescent protein reports the expression of dopamine D1 or D2 receptors. After recovery of the neurons, the tissue was immunolabelled for vesicular glutamate transporters type 1 and 2, as markers of cortical and thalamic terminals, respectively. Three of each class of MSNs were reconstructed in 3D and second-order dendrites selected for electron microscopic analysis. Our findings show that direct and indirect pathway MSNs, located in the matrix compartment of the striatum, receive convergent input from cortex and thalamus preferentially on their spines. There were no differences in the pattern of innervation of direct and indirect pathway MSNs, but the cortical input is more prominent in both and synaptic density is greater for direct pathway neurons. The 3D reconstructions revealed no morphological differences between direct and indirect MSNs. Overall, our findings demonstrate that direct and indirect pathway MSNs located in the matrix receive convergent cortical and thalamic input and suggest that both cortical and thalamic inputs are involved in the activation of MSNs.

Sleep and the single neuron: the role of global slow oscillations in individual cell rest

Sleep is universal in animals, but its specific functions remain elusive. We propose that sleep's primary function is to allow individual neurons to perform prophylactic cellular maintenance. Just as muscle cells must rest after strenuous exercise to prevent long-term damage, brain cells must rest after intense synaptic activity. We suggest that periods of reduced synaptic input ('off periods' or 'down states') are necessary for such maintenance. This in turn requires a state of globally synchronized neuronal activity, reduced sensory input and behavioural immobility - the well-known manifestations of sleep.

Up states are rare in awake auditory cortex

The dynamics of subthreshold membrane potential provide insight into the organization of activity in neural circuits. In many brain areas, membrane potential is bistable, transiting between a relatively hyperpolarized down state and a depolarized up state. These up and down states, which have been proposed to play a number of computational roles, have mainly been studied in anesthetized and in vitro preparations. Here, we have used intracellular recordings to characterize the dynamics of membrane potential in the auditory cortex of awake rats. We find that long up states are rare in the awake auditory cortex, with only 0.4% of up states >500 ms. Most neurons displayed only brief up states (bumps) and spent on average ∼1% of recording time in up states >500 ms. We suggest that the near absence of long up states in awake auditory cortex may reflect an adaptation to the rapid processing of auditory stimuli.

Characteristic changes in the slow cortical waves after a 6-h sleep deprivation in rat

Sleep deprivation is followed by an increase in EEG delta power during recovery sleep indicating an increased sleep propensity. Delta waves mostly reflect the rhythmic recurring of generalized hyperpolarizations (DOWN state) in cortical neurons causing large, deep-positive waves in the LFP. Enhancement of delta power in recovery sleep can be the consequence of either the more frequent occurrence, or the higher amplitude caused by higher synchrony, or the longer duration of these DOWN states. In the present experiments, we examined these possibilities and found the strongest increase in the incidence of slow deep positive LFP waves (slow waves) following sleep deprivation indicating enhancement of DOWN state inducing and/or weakening of UP state maintaining processes. The strong decrease in multiunit activity during slow waves was preceded by a gradual buildup of activity. The significant correlation between these changes both in control and recovery recordings indicate that excitation might determine the subsequent drop in activity. Increased sensitivity of cortical neurons to excitation might offer an explanation for this observation. Current-source-density analysis indicated in our experiments that the first sources during DOWN states appeared in layer III-IV. Activation was then displaced to layer V. In the motor cortex, both corticocortical and thalamocortical fibers terminate in layer III that provides a strong feedforward excitation to layer V. As propagation of facilitatory signals through cortical layers is downwardly biased, disfacilitation might also follow this pattern. Sleep deprivation caused only quantitative differences in the sink-source patterns, indicating that existing processes were enhanced by sleep deprivation.

Populations of striatal medium spiny neurons encode vibrotactile frequency in rats: modulation by slow wave oscillations

Dorsolateral striatum (DLS) is implicated in tactile perception and receives strong projections from somatosensory cortex. However, the sensory representations encoded by striatal projection neurons are not well understood. Here we characterized the contribution of DLS to the encoding of vibrotactile information in rats by assessing striatal responses to precise frequency stimuli delivered to a single vibrissa. We applied stimuli in a frequency range (45-90 Hz) that evokes discriminable percepts and carries most of the power of vibrissa vibration elicited by a range of complex fine textures. Both medium spiny neurons and evoked potentials showed tactile responses that were modulated by slow wave oscillations. Furthermore, medium spiny neuron population responses represented stimulus frequency on par with previously reported behavioral benchmarks. Our results suggest that striatum encodes frequency information of vibrotactile stimuli which is dynamically modulated by ongoing brain state.

Relationships between the firing of identified striatal interneurons and spontaneous and driven cortical activities in vivo

The striatum is comprised of medium-sized spiny projection neurons (MSNs) and several types of interneuron, and receives massive glutamatergic input from the cerebral cortex. Understanding of striatal function requires definition of the electrophysiological properties of neurochemically identified interneurons sampled in the same context of ongoing cortical activity in vivo. To address this, we recorded the firing of cholinergic interneurons (expressing choline acetyltransferase; ChAT) and GABAergic interneurons expressing parvalbumin (PV) or nitric oxide synthase (NOS), as well as MSNs, in anesthetized rats during cortically defined brain states. Depending on the cortical state, these interneurons were partly distinguished from each other, and MSNs, on the basis of firing rate and/or pattern. During slow-wave activity (SWA), ChAT+ interneurons, and some PV+ and NOS+ interneurons, were tonically active; NOS+ interneurons fired prominent bursts but, contrary to investigations in vitro, these were not typical low-threshold spike bursts. Identified MSNs, and other PV+ and NOS+ interneurons, were phasically active. Contrasting with ChAT+ interneurons, whose firing showed poor brain state dependency, PV+ and NOS+ interneurons displayed robust firing increases and decreases, respectively, upon spontaneous or driven transitions from SWA to cortical activation. The firing of most neurons was phase locked to cortical slow oscillations, but only PV+ and ChAT+ interneurons also fired in time with cortical spindle and gamma oscillations. Complementing this diverse temporal coupling, each interneuron type exhibited distinct responses to cortical stimulation. Thus, these striatal interneuron types have distinct temporal signatures in vivo, including relationships to spontaneous and driven cortical activities, which likely underpin their specialized contributions to striatal microcircuit function.

Origins of 1/f2 scaling in the power spectrum of intracortical local field potential

It has been noted that the power spectrum of intracortical local field potential (LFP) often scales as 1/f−2. It is thought that LFP mostly represents the spiking-related neuronal activity such as synaptic currents and spikes in the vicinity of the recording electrode, but no 1/f2 scaling is detected in the spike power. Although tissue filtering or modulation of spiking activity by UP and DOWN states could account for the observed LFP scaling, there is no consensus as to how it arises. We addressed this question by recording simultaneously LFP and single neurons (“single units”) from multiple sites in somatosensory cortex of anesthetized rats. Single-unit data revealed the presence of periods of high activity, presumably corresponding to the “UP” states when the neuronal membrane potential is depolarized, and periods of no activity, the putative “DOWN” states when the membrane potential is close to resting. As expected, the LFP power scaled as 1/f2 but no such scaling was found in the power spectrum of spiking activity. Our analysis showed that 1/f2 scaling in the LFP power spectrum was largely generated by the steplike transitions between UP and DOWN states. The shape of the LFP signal during these transitions, but not the transition timing, was crucial to obtain the observed scaling. These transitions were probably induced by synchronous changes in the membrane potential across neurons. We conclude that a 1/f2 scaling in the LFP power indicates the presence of steplike transitions in the LFP trace and says little about the statistical properties of the associated neuronal firing.

Cholinergic modulation of slow cortical rhythm in urethane-anesthetized rats

Slow cortical rhythm (SCR) is characterized by rhythmic cycling of active (UP) and silent (DOWN) states in cortical cells. In urethane anesthesia, SCR appears as alternation of almost isoelectrical EEG periods and low-frequency, high-amplitude large shifts with superimposed high-frequency activity in the local field potentials (LFPs). Dense cholinergic projection reaches the cortex from the basal forebrain (BF), and acetylcholine (ACh) has been demonstrated to play a crucial role in the regulation of cortical activity. In the present experiments, cholinergic drugs were administered topically to the cortical surface of urethane-anesthetized rats to examine the direct involvement of ACh and the BF cholinergic system in the SCR. SCR was recorded by a 16-pole vertical electrode array from the hindlimb area of the somatosensory cortex. Multiple unit activity (MUA) was recorded from layer V to VI in close proximity of the recording array. Neither a low dose (10 mM solution) of the muscarinic antagonist atropine or the nicotinic agonist nicotine (1 mM solution) had any effect on SCR. In contrast, the higher dose (100 mM solution) of atropine, the cholinergic agonist carbachol (32 mM solution), and the cholinesterase inhibitor physostigmine (13 mM solution) all decreased the number of UP states, delta power (0-3 Hz) and MUA. These results suggest that cholinergic system may influence SCR through muscarinic mechanisms during urethane anesthesia. Cholinergic activation obstructs the mechanisms responsible for local or global synchronization seen during SCR as this rhythm was disrupted or aborted. Muscarinic antagonism can evoke similar changes when high dose of atropine is applied.

Stereotypical spatiotemporal activity patterns during slow-wave activity in the neocortex

Alternating epochs of activity and silence are a characteristic feature of neocortical networks during certain sleep cycles and deep states of anesthesia. The mechanism and functional role of these slow oscillations (<1 Hz) have not yet been fully characterized. Experimental and theoretical studies show that slow-wave oscillations can be generated autonomously by neocortical tissue but become more regular through a thalamo-cortical feedback loop. Evidence for a functional role of slow-wave activity comes from EEG recordings in humans during sleep, which show that activity travels as stereotypical waves over the entire brain, thought to play a role in memory consolidation. We used an animal model to investigate activity wave propagation on a smaller scale, namely within the rat somatosensory cortex. Signals from multiple extracellular microelectrodes in combination with one intracellular recording in the anesthetized animal in vivo were utilized to monitor the spreading of activity. We found that activity propagation in most animals showed a clear preferred direction, suggesting that it often originated from a similar location in the cortex. In addition, the breakdown of active states followed a similar pattern with slightly weaker direction preference but a clear correlation to the direction of activity spreading, supporting the notion of a wave-like phenomenon similar to that observed after strong sensory stimulation in sensory areas. Taken together, our findings support the idea that activity waves during slow-wave sleep do not occur spontaneously at random locations within the network, as was suggested previously, but follow preferred synaptic pathways on a small spatial scale.

Cortical state and attention

The brain continuously adapts its processing machinery to behavioural demands. To achieve this, it rapidly modulates the operating mode of cortical circuits, controlling the way that information is transformed and routed. This article will focus on two experimental approaches by which the control of cortical information processing has been investigated: the study of state-dependent cortical processing in rodents and attention in the primate visual system. Both processes involve a modulation of low-frequency activity fluctuations and spiking correlation, and are mediated by common receptor systems. We suggest that selective attention involves processes that are similar to state change, and that operate at a local columnar level to enhance the representation of otherwise non-salient features while suppressing internally generated activity patterns.

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.

Spatiotemporal scales and links between electrical neuroimaging modalities

Recordings of brain electrophysiological activity provide the most direct reflect of neural function. Information contained in these signals varies as a function of the spatial scale at which recordings are done: from single cell recording to large scale macroscopic fields, e.g., scalp EEG. Microscopic and macroscopic measurements and models in Neuroscience are often in conflict. Solving this conflict might require the developments of a sort of bio-statistical physics, a framework for relating the microscopic properties of individual cells to the macroscopic or bulk properties of neural circuits. Such a framework can only emerge in Neuroscience from the systematic analysis and modeling of the diverse recording scales from simultaneous measurements. In this article we briefly review the different measurement scales and models in modern neuroscience to try to identify the sources of conflict that might ultimately help to create a unified theory of brain electromagnetic fields. We argue that seen the different recording scales, from the single cell to the large scale fields measured by the scalp electroencephalogram, as derived from a unique physical magnitude--the electric potential that is measured in all cases--might help to conciliate microscopic and macroscopic models of neural function as well as the animal and human neuroscience literature.

Sensory input drives multiple intracellular information streams in somatosensory cortex

Stable perception arises from the interaction between sensory inputs and internal activity fluctuations in cortex. Here we analyzed how different types of activity contribute to cortical sensory processing at the cellular scale. We performed whole-cell recordings in the barrel cortex of anesthetized rats while applying ongoing whisker stimulation and measured the information conveyed about the time-varying stimulus by different types of input (membrane potential) and output (spiking) signals. We found that substantial, comparable amounts of incoming information are carried by two types of membrane potential signal: slow, large (up-down state) fluctuations, and faster (>20 Hz), smaller-amplitude synaptic activity. Both types of activity fluctuation are therefore significantly driven by the stimulus on an ongoing basis. Each stream conveys essentially independent information. Output (spiking) information is contained in spike timing not just relative to the stimulus but also relative to membrane potential fluctuations. Information transfer is favored in up states relative to down states. Thus, slow, ongoing activity fluctuations and finer-scale synaptic activity generate multiple channels for incoming and outgoing information within barrel cortex neurons during ongoing stimulation.