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

Propagating population activity patterns during spontaneous slow waves in the thalamus of rodents

Slow waves (SWs) represent the most prominent electrophysiological events in the thalamocortical system under anesthesia and during deep sleep. Recent studies have revealed that SWs have complex spatiotemporal dynamics and propagate across neocortical regions. However, it is still unclear whether neuronal activity in the thalamus exhibits similar propagation properties during SWs. Here, we report propagating population activity in the thalamus of ketamine/xylazine-anesthetized rats and mice visualized by high-density silicon probe recordings. In both rodent species, propagation of spontaneous thalamic activity during up-states was most frequently observed in dorsal thalamic nuclei such as the higher order posterior (Po), lateral posterior (LP) or laterodorsal (LD) nuclei. The preferred direction of thalamic activity spreading was along the dorsoventral axis, with over half of the up-states exhibiting a gradual propagation in the ventral-to-dorsal direction. Furthermore, simultaneous neocortical and thalamic recordings collected under anesthesia demonstrated that there is a weak but noticeable interrelation between propagation patterns observed during cortical up-states and those displayed by thalamic population activity. In addition, using chronically implanted silicon probes, we detected propagating activity patterns in the thalamus of naturally sleeping rats during slow-wave sleep. However, in comparison to propagating up-states observed under anesthesia, these propagating patterns were characterized by a reduced rate of occurrence and a faster propagation speed. Our findings suggest that the propagation of spontaneous population activity is an intrinsic property of the thalamocortical network during synchronized brain states such as deep sleep or anesthesia. Additionally, our data implies that the neocortex may have partial control over the formation of propagation patterns within the dorsal thalamus under anesthesia.

Slow Waves in Cortical Slices: How Spontaneous Activity is Shaped by Laminar Structure

Cortical slow oscillations (SO) of neural activity spontaneously emerge and propagate during deep sleep and anesthesia and are also expressed in isolated brain slices and cortical slabs. We lack full understanding of how SO integrate the different structural levels underlying local excitability of cell assemblies and their mutual interaction. Here, we focus on ongoing slow waves (SWs) in cortical slices reconstructed from a 16-electrode array designed to probe the neuronal activity at multiple spatial scales. In spite of the variable propagation patterns observed, we reproducibly found a smooth strip of loci leading the SW fronts, overlapping cortical layers 4 and 5, along which Up states were the longest and displayed the highest firing rate. Propagation modes were uncorrelated in time, signaling a memoryless generation of SWs. All these features could be modeled by a multimodular large-scale network of spiking neurons with a specific balance between local and intermodular connectivity. Modules work as relaxation oscillators with a weakly stable Down state and a peak of local excitability to model layers 4 and 5. These conditions allow for both optimal sensitivity to the network structure and richness of propagation modes, both of which are potential substrates for dynamic flexibility in more general contexts.

Direct pathway neurons in mouse dorsolateral striatum in vivo receive stronger synaptic input than indirect pathway neurons

Striatal projection neurons, the medium spiny neurons (MSNs), play a crucial role in various motor and cognitive functions. MSNs express either D1- or D2-type dopamine receptors and initiate the direct-pathway (dMSNs) or indirect pathways (iMSNs) of the basal ganglia, respectively. dMSNs have been shown to receive more inhibition than iMSNs from intrastriatal sources. Based on these findings, computational modeling of the striatal network has predicted that under healthy conditions dMSNs should receive more total input than iMSNs. To test this prediction, we analyzed in vivo whole cell recordings from dMSNs and iMSNs in healthy and dopamine-depleted (6OHDA) anaesthetized mice. By comparing their membrane potential fluctuations, we found that dMSNs exhibited considerably larger membrane potential fluctuations over a wide frequency range. Furthermore, by comparing the spike-triggered average membrane potentials, we found that dMSNs depolarized toward the spike threshold significantly faster than iMSNs did. Together, these findings (in particular the STA analysis) corroborate the theoretical prediction that direct-pathway MSNs receive stronger total input than indirect-pathway neurons. Finally, we found that dopamine-depleted mice exhibited no difference between the membrane potential fluctuations of dMSNs and iMSNs. These data provide new insights into the question of how the lack of dopamine may lead to behavioral deficits associated with Parkinson’s disease.

NEW & NOTEWORTHY The direct and indirect pathways of the basal ganglia originate from the D1- and D2-type dopamine receptor expressing medium spiny neurons (dMSNs and iMSNs). Theoretical results have predicted that dMSNs should receive stronger synaptic input than iMSNs. Using in vivo intracellular membrane potential data, we provide evidence that dMSNs indeed receive stronger input than iMSNs, as has been predicted by the computational model.

Focused transcranial ultrasound for treatment of neurodegenerative dementia

Introduction

Preclinical studies support investigation of focused ultrasound for breakdown of cerebral pathologies in neurodegenerative conditions including Alzheimer's disease (AD) and Parkinson's disease (PD).

Methods

A focused transcranial Doppler device with probes (2 MHz, 520 mW/cm²) affixed bilaterally was used to target the hippocampus (AD) or substantia nigra (PD) with functional magnetic resonance imaging navigation for enhanced plaque removal. A total of 22 patients (n = 11 AD, n = 11 PD) underwent 8 consecutive, weekly, 1-hour treatments wherein sleep was encouraged naturally or pharmacologically. Cognitive and motor functioning assessment was carried out using standardized evaluations at baseline and conclusion.

Results

Of all, 62.5% of patients had one or more improved cognitive scores without data incongruence, 87% had stable or improved fine motor scores, and 87.5% had stable or improved gross motor scores. No adverse events were reported.

Discussion

The safety of focused transcranial Doppler and possible enhancement in patient functioning were suggested by outcome data.

New waves: Rhythmic electrical field stimulation systematically alters spontaneous slow dynamics across mouse neocortex

The signature rhythm of slow-wave forebrain activity is the large amplitude, slow oscillation (SO: ∼1 Hz) made up of alternating synchronous periods of activity and silence at the single cell and network levels. On each wave, the SO originates at a unique location and propagates across the neocortex. Attempts to manipulate SO activity using electrical fields have been shown to entrain cortical networks and enhance memory performance. However, neural activity during this manipulation has remained elusive due to methodological issues in typical electrical recordings. Here we took advantage of voltage-sensitive dye (VSD) imaging in a bilateral cortical preparation of urethane-anesthetized mice to track SO cortical activity and its modulation by sinusoidal electrical field stimulation applied to frontal regions. We show that under spontaneous conditions, the SO propagates in two main opposing directional patterns along an anterior lateral - posterior medial axis, displaying a rich variety of possible trajectories on any given wave. Under rhythmic field stimulation, new propagation patterns emerge, which are not observed under spontaneous conditions, reflecting stimulus-entrained activity with distributed and varied anterior initiation zones and a consistent termination zone in the posterior somatosensory cortex. Furthermore, stimulus-induced activity patterns tend to repeat cycle after cycle, showing higher stereotypy than during spontaneous activity. Our results show that slow electrical field stimulation robustly entrains and alters ongoing slow cortical dynamics during sleep-like states, suggesting a mechanism for targeting specific cortical representations to manipulate memory processes.

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.

Cortical Dynamics in Presence of Assemblies of Densely Connected Weight-Hub Neurons

Experimental measurements of pairwise connection probability of pyramidal neurons together with the distribution of synaptic weights have been used to construct randomly connected model networks. However, several experimental studies suggest that both wiring and synaptic weight structure between neurons show statistics that differ from random networks. Here we study a network containing a subset of neurons which we call weight-hub neurons, that are characterized by strong inward synapses. We propose a connectivity structure for excitatory neurons that contain assemblies of densely connected weight-hub neurons, while the pairwise connection probability and synaptic weight distribution remain consistent with experimental data. Simulations of such a network with generalized integrate-and-fire neurons display regular and irregular slow oscillations akin to experimentally observed up/down state transitions in the activity of cortical neurons with a broad distribution of pairwise spike correlations. Moreover, stimulation of a model network in the presence or absence of assembly structure exhibits responses similar to light-evoked responses of cortical layers in optogenetically modified animals. We conclude that a high connection probability into and within assemblies of excitatory weight-hub neurons, as it likely is present in some but not all cortical layers, changes the dynamics of a layer of cortical microcircuitry significantly.

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.

Lag threads organize the brain's intrinsic activity

It has been widely reported that intrinsic brain activity, in a variety of animals including humans, is spatiotemporally structured. Specifically, propagated slow activity has been repeatedly demonstrated in animals. In human resting-state fMRI, spontaneous activity has been understood predominantly in terms of zero-lag temporal synchrony within widely distributed functional systems (resting-state networks). Here, we use resting-state fMRI from 1,376 normal, young adults to demonstrate that multiple, highly reproducible, temporal sequences of propagated activity, which we term "lag threads," are present in the brain. Moreover, this propagated activity is largely unidirectional within conventionally understood resting-state networks. Modeling experiments show that resting-state networks naturally emerge as a consequence of shared patterns of propagation. An implication of these results is that common physiologic mechanisms may underlie spontaneous activity as imaged with fMRI in humans and slowly propagated activity as studied in animals.

Wave propagation of cortical population activity under urethane anesthesia is state dependent

BACKGROUND

Propagating waves of excitation have been observed extensively in the neocortex, during both spontaneous and sensory-evoked activity, and they play a critical role in spatially organizing information processing. However, the state-dependence of these spatiotemporal propagation patterns is largely unexplored. In this report, we use voltage-sensitive dye imaging in the rat visual cortex to study the propagation of spontaneous population activity in two discrete cortical states induced by urethane anesthesia.

RESULTS

While laminar current source density patterns of spontaneous population events in these two states indicate a considerable degree of similarity in laminar networks, lateral propagation in the more active desynchronized state is approximately 20% faster than in the slower synchronized state. Furthermore, trajectories of wave propagation exhibit a strong anisotropy, but the preferred direction is different depending on cortical state.

CONCLUSIONS

Our results show that horizontal wave propagation of spontaneous neural activity is largely dependent on the global activity states of local cortical circuits.

Population-wide bias of surround suppression in auditory spatial receptive fields of the owl's midbrain

The physical arrangement of receptive fields (RFs) within neural structures is important for local computations. Nonuniform distribution of tuning within populations of neurons can influence emergent tuning properties, causing bias in local processing. This issue was studied in the auditory system of barn owls. The owl's external nucleus of the inferior colliculus (ICx) contains a map of auditory space in which the frontal region is overrepresented. We measured spatiotemporal RFs of ICx neurons using spatial white noise. We found a population-wide bias in surround suppression such that suppression from frontal space was stronger. This asymmetry increased with laterality in spatial tuning. The bias could be explained by a model of lateral inhibition based on the overrepresentation of frontal space observed in ICx. The model predicted trends in surround suppression across ICx that matched the data. Thus, the uneven distribution of spatial tuning within the map could explain the topography of time-dependent tuning properties. This mechanism may have significant implications for the analysis of natural scenes by sensory systems.

EEG-fMRI Methods for the Study of Brain Networks during Sleep

Modern neuroimaging methods may provide unique insights into the mechanism and role of sleep, as well as into particular mechanisms of brain function in general. Many of the recent neuroimaging studies have used concurrent EEG and fMRI, which present unique technical challenges ranging from the difficulty of inducing sleep in the MRI environment to appropriate instrumentation and data processing methods to obtain artifact free data. In addition, the use of EEG-fMRI during sleep leads to unique data interpretation issues, as common approaches developed for the analysis of task-evoked activity do not apply to sleep. Reviewed are a variety of statistical approaches that can be used to characterize brain activity from fMRI data acquired during sleep, with an emphasis on approaches that investigate the presence of correlated activity between brain regions. Each of these approaches has advantages and disadvantages that must be considered in concert with the theoretical questions of interest. Specifically, fundamental theories of sleep control and function should be considered when designing these studies and when choosing the associated statistical approaches. For example, the notion that local brain activity during sleep may be triggered by local, use-dependent activity during wakefulness may be tested by analyzing sleep networks as statistically independent components. Alternatively, the involvement of regions in more global processes such as arousal may be investigated with correlation analysis.