Unique Transcriptomic Cell Types of the Granular Retrosplenial Cortex are Preserved Across Mice and Rats Despite Dramatic Changes in Key Marker Genes.

The granular retrosplenial cortex (RSG) supports key functions ranging from memory consolidation to spatial navigation. The mouse RSG contains several cell types that are remarkably distinct from those found in other cortical regions. This includes the physiologically and transcriptomically unique low rheobase neuron that is the dominant cell-type in RSG layers 2/3 (L2/3 LR), as well as the similarly exclusive pyramidal cells that comprise much of RSG layer 5a (L5a RSG). While the functions of the RSG are extensively studied in both mice and rats, it remains unknown if the transcriptomically unique cell types of the mouse RSG are evolutionarily conserved in rats. Here, we show that mouse and rat RSG not only contain the same cell types, but key subtypes including the L2/3 LR and L5a RSG neurons are amplified in their representations in rats compared to mice. This preservation of cell types in male and female rats happens despite dramatic changes in key cell-type-specific marker genes, with the Scnn1a expression that selectively tags mouse L5a RSG neurons completely absent in rats. Important for Cre-driver line development, we identify alternative, cross-species genes that can be used to selectively target the cell types of the RSG in both mice and rats. Our results show that the unique cell types of the RSG are evolutionarily conserved across millions of years of evolution between mice and rats, but also emphasize stark species-specific differences in marker genes that need to be considered when making cell-type-specific transgenic lines of mice versus rats.

Cell-type-specific cholinergic control of granular retrosplenial cortex with implications for angular velocity coding across brain states.

Cholinergic receptor activation enables the persistent firing of cortical pyramidal neurons, providing a key cellular basis for theories of spatial navigation involving working memory, path integration, and head direction encoding. The granular retrosplenial cortex (RSG) is important for spatially-guided behaviors, but how acetylcholine impacts RSG neurons is unknown. Here, we show that a transcriptomically, morphologically, and biophysically distinct RSG cell-type - the low-rheobase (LR) neuron - has a very distinct expression profile of cholinergic muscarinic receptors compared to all other neighboring excitatory neuronal subtypes. LR neurons do not fire persistently in response to cholinergic agonists, in stark contrast to all other principal neuronal subtypes examined within the RSG and across midline cortex. This lack of persistence allows LR neuron models to rapidly compute angular head velocity (AHV), independent of cholinergic changes seen during navigation. Thus, LR neurons can consistently compute AHV across brain states, highlighting the specialized RSG neural codes supporting navigation.

Cellular rules underlying psychedelic control of prefrontal pyramidal neurons.

Classical psychedelic drugs are thought to increase excitability of pyramidal cells in prefrontal cortex via activation of serotonin 2A receptors (5-HT2ARs). Here, we instead find that multiple classes of psychedelics dose-dependently suppress intrinsic excitability of pyramidal neurons, and that extracellular delivery of psychedelics decreases excitability significantly more than intracellular delivery. A previously unknown mechanism underlies this psychedelic drug action: enhancement of ubiquitously expressed potassium "M-current" channels that is independent of 5-HT2R activation. Using machine-learning-based data assimilation models, we show that M-current activation interacts with previously described mechanisms to dramatically reduce intrinsic excitability and shorten working memory timespan. Thus, psychedelic drugs suppress intrinsic excitability by modulating ion channels that are expressed throughout the brain, potentially triggering homeostatic adjustments that can contribute to widespread therapeutic benefits.

Running speed and REM sleep control two distinct modes of rapid interhemispheric communication.

Rhythmic gamma-band communication within and across cortical hemispheres is critical for optimal perception, navigation, and memory. Here, using multisite recordings in both rats and mice, we show that even faster ∼140 Hz rhythms are robustly anti-phase across cortical hemispheres, visually resembling splines, the interlocking teeth on mechanical gears. Splines are strongest in superficial granular retrosplenial cortex, a region important for spatial navigation and memory. Spline-frequency interhemispheric communication becomes more coherent and more precisely anti-phase at faster running speeds. Anti-phase splines also demarcate high-activity frames during REM sleep. While splines and associated neuronal spiking are anti-phase across retrosplenial hemispheres during navigation and REM sleep, gamma-rhythmic interhemispheric communication is precisely in-phase. Gamma and splines occur at distinct points of a theta cycle and thus highlight the ability of interhemispheric cortical communication to rapidly switch between in-phase (gamma) and anti-phase (spline) modes within individual theta cycles during both navigation and REM sleep.

Thalamus and claustrum control parallel layer 1 circuits in retrosplenial cortex.

The granular retrosplenial cortex (RSG) is critical for both spatial and non-spatial behaviors, but the underlying neural codes remain poorly understood. Here, we use optogenetic circuit mapping in mice to reveal a double dissociation that allows parallel circuits in superficial RSG to process disparate inputs. The anterior thalamus and dorsal subiculum, sources of spatial information, strongly and selectively recruit small low-rheobase (LR) pyramidal cells in RSG. In contrast, neighboring regular-spiking (RS) cells are preferentially controlled by claustral and anterior cingulate inputs, sources of mostly non-spatial information. Precise sublaminar axonal and dendritic arborization within RSG layer 1, in particular, permits this parallel processing. Observed thalamocortical synaptic dynamics enable computational models of LR neurons to compute the speed of head rotation, despite receiving head direction inputs that do not explicitly encode speed. Thus, parallel input streams identify a distinct principal neuronal subtype ideally positioned to support spatial orientation computations in the RSG.

Sitting in your car, about to drive home after a long day at work, you realize you have no idea which way to go: you recognize where you are right now, and you remember the name of the street your house is on, but you cannot figure out how to get there. This spatial disorientation happens to people with damage to a brain region called the retrosplenial cortex, whose role and inner workings remain poorly understood. Recent evidence has shown that this area contains 'low-rheobase' neurons which are not seen anywhere else in the brain, but what do these neurons do? Brennan, Jedrasiak-Cape, Kailasa et al. decided to explore the role of these neurons, focusing on the brain regions they are connected to. Experiments were conducted in mice using optogenetics, a technique that activates neurons using pulses of light. This revealed that brain areas involved in processing information about direction and position preferentially communicate with low-rheobase neurons rather than with nearby, more standard neurons in the retrosplenial cortex. The way these spatial signals are sent to the low-rheobase neurons allows these cells to 'calculate' how fast a mouse is turning its head using only information about which direction the mouse is facing. Essentially, this neuron can turn directional compass-like signals into a gyroscope signal that can track both direction and speed of head movement. These unique neurons may therefore be ideally suited to combine information about direction and space, suggesting that they may have evolved specifically to support spatial navigation. Individuals with Alzheimer's disease show exactly the same type of spatial disorientation as individuals with direct damage to the retrosplenial cortex. This region is also one of the first to show altered activity in Alzheimer's disease. Exploring whether these unique retrosplenial neurons and their communication patterns are altered in Alzheimer's disease models could help to understand and potentially treat this debilitating condition.

Dynamics of recovery from anaesthesia-induced unconsciousness across primate neocortex.

How the brain recovers from general anaesthesia is poorly understood. Neurocognitive problems during anaesthesia recovery are associated with an increase in morbidity and mortality in patients. We studied intracortical neuronal dynamics during transitions from propofol-induced unconsciousness into consciousness by directly recording local field potentials and single neuron activity in a functionally and anatomically interconnecting somatosensory (S1, S2) and ventral premotor (PMv) network in primates. Macaque monkeys were trained for a behavioural task designed to determine trial-by-trial alertness and neuronal response to tactile and auditory stimulation. We found that neuronal dynamics were dissociated between S1 and higher-order PMv prior to return of consciousness. The return of consciousness was distinguishable by a distinctive return of interregionally coherent beta oscillations and disruption of the slow-delta oscillations. Clustering analysis demonstrated that these state transitions between wakefulness and unconsciousness were rapid and unstable. In contrast, return of pre-anaesthetic task performance was observed with a gradual increase in the coherent beta oscillations. We also found that recovery end points significantly varied intra-individually across sessions, as compared to a rather consistent loss of consciousness time. Recovery of single neuron multisensory responses appeared to be associated with the time of full performance recovery rather than the length of recovery time. Similar to loss of consciousness, return of consciousness was identified with an abrupt shift of dynamics and the regions were dissociated temporarily during the transition. However, the actual dynamics change during return of consciousness is not simply an inverse of loss of consciousness, suggesting a unique process.

Hyperexcitable Neurons Enable Precise and Persistent Information Encoding in the Superficial Retrosplenial Cortex.

The retrosplenial cortex (RSC) is essential for memory and navigation, but the neural codes underlying these functions remain largely unknown. Here, we show that the most prominent cell type in layers 2/3 (L2/3) of the mouse granular RSC is a hyperexcitable, small pyramidal cell. These cells have a low rheobase (LR), high input resistance, lack of spike frequency adaptation, and spike widths intermediate to those of neighboring fast-spiking (FS) inhibitory neurons and regular-spiking (RS) excitatory neurons. LR cells are excitatory but rarely synapse onto neighboring neurons. Instead, L2/3 is a feedforward, not feedback, inhibition-dominated network with dense connectivity between FS cells and from FS to LR neurons. Biophysical models of LR but not RS cells precisely and continuously encode sustained input from afferent postsubicular head-direction cells. Thus, the distinct intrinsic properties of LR neurons can support both the precision and persistence necessary to encode information over multiple timescales in the RSC.

The neural circuitry supporting successful spatial navigation despite variable movement speeds.

Ants who have successfully navigated the long distance between their foraging spot and their nest dozens of times will drastically overshoot their destination if the size of their legs is doubled by the addition of stilts. This observation reflects a navigational strategy called path integration, a strategy also utilized by mammals. Path integration necessitates that animals keep track of their movement speed and use it to precisely and instantly modify where they think they are and where they want to go. Here we review the neural circuitry that has evolved to integrate speed and space. We start with the rate and temporal codes for speed in the hippocampus and work backwards towards the motor and sensory systems. We highlight the need for experiments designed to differentiate the respective contributions of motor efference copy versus sensory inputs. In particular, we discuss the importance of high-resolution tracking of the latency of speed-encoding as a precise way to disentangle the sensory versus motor computations that enable successful spatial navigation at very different speeds.

Neural circuits linking sleep and addiction: Animal models to understand why select individuals are more vulnerable to substance use disorders after sleep deprivation.

Individuals differ widely in their drug-craving behaviors. One reason for these differences involves sleep. Sleep disturbances lead to an increased risk of substance use disorders and relapse in only some individuals. While animal studies have examined the impact of sleep on reward circuitry, few have addressed the role of individual differences in the effects of altered sleep. There does, however, exist a rodent model of individual differences in reward-seeking behavior: the sign/goal-tracker model of Pavlovian conditioned approach. In this model, only some rats show the key behavioral traits associated with addiction, including impulsivity and poor attentional control, making this an ideal model system to examine individually distinct sleep-reward interactions. Here, we describe how the limbic neural circuits responsible for individual differences in incentive motivation overlap with those involved in sleep-wake regulation, and how this model can elucidate the common underlying mechanisms. Consideration of individual differences in preclinical models would improve our understanding of how sleep interacts with motivational systems, and why sleep deprivation contributes to addiction in only select individuals.

Instantaneous amplitude and shape of postrhinal theta oscillations differentially encode running speed.

Hippocampal theta oscillations have a temporally asymmetric waveform shape, but it is not known if this theta asymmetry extends to all other cortical regions involved in spatial navigation and memory. Here, using both established and improved cycle-by-cycle analysis methods, we show that theta waveforms in the postrhinal cortex are also temporally asymmetric. On average, the falling phase of postrhinal theta cycles lasts longer than the subsequent rising phase. There are, however, rapid changes in both the instantaneous amplitude and instantaneous temporal asymmetry of postrhinal theta cycles. These rapid changes in amplitude and asymmetry are very poorly correlated, indicative of a mechanistic disconnect between these theta cycle features. We show that the instantaneous amplitude and asymmetry of postrhinal theta cycles differentially encode running speed. Although theta amplitude continues to increase at the fastest running speeds, temporal asymmetry of the theta waveform shape plateaus after medium speeds. Our results suggest that the amplitude and waveform shape of individual postrhinal theta cycles may be governed by partially independent mechanisms and emphasize the importance of employing a single cycle approach to understanding the genesis and behavioral correlates of cortical theta rhythms. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Ripple While You Walk, and You May Get Lost: Pathological High-Frequency Activity Can Alter Spatial Navigation Circuits.

[Box: see text].

More Is More: Potential Benefits of Characterizing High-Frequency Activity Over Long Durations.

[Box: see text].

High-Frequency Activity During Stereotyped Low-Frequency Events Might Help to Identify the Seizure Onset Zone.

Stereotyped high-frequency oscillations discriminate seizure onset zones and critical functional cortex in focal epilepsy. Liu S, Gurses C, Sha Z, Quach MM, Sencer A, Bebek N, et al. Brain. 2018;141(3):713-730. doi:10.1093/brain/awx374. PMID: 29394328 . High-frequency oscillations in local field potentials recorded with intracranial electroencephalogram are putative biomarkers of seizure-onset zones in epileptic brain. However, localized 80- to 500-Hz oscillations can also be recorded from normal and nonepileptic cerebral structures. When defined only by rate or frequency, physiological high-frequency oscillations are indistinguishable from pathological ones that limit their application in epilepsy presurgical planning. We hypothesized that pathological high-frequency oscillations occur in a repetitive fashion with a similar waveform morphology that specifically indicates seizure onset zones. We investigated the waveform patterns of automatically detected high-frequency oscillations in 13 patients with epilepsy and 5 control subjects, with an average of 73 subdural and intracerebral electrodes recorded per patient. The repetitive oscillatory waveforms were identified using a pipeline of unsupervised machine learning techniques and were then correlated with independently clinician-defined seizure onset zones. Consistently in all patients, the stereotypical high-frequency oscillations with the highest degree of waveform similarity were localized within the seizure onset zones only, whereas the channels generating high-frequency oscillations embedded in random waveforms were found in the functional regions independent of the epileptogenic locations. The repetitive waveform pattern was more evident in fast ripples compared to ripples, suggesting a potential association between waveform repetition and the underlying pathological network. Our findings provided a new tool for the interpretation of pathological high-frequency oscillations that can be efficiently applied to distinguish seizure onset zones from functionally important sites, which is a critical step toward the translation of these signature events into valid clinical biomarkers.

A Straw Can Break a Neural Network's Back and Lead to Seizures-But Only When Delivered at the Right Time.

Loss of Neuronal Network Resilience Precedes Seizures and Determines the Ictogenic Nature of Interictal Synaptic Perturbations Chang WC, Kudlacek J, Hlinka J, et al. Nat Neurosci. 2018; 21(12):1742-1752. doi:10.1038/s41593-018-0278-y. PMID: 30482946. The mechanism of seizure emergence and the role of brief interictal epileptiform discharges (IEDs) in seizure generation are 2 of the most important unresolved issues in modern epilepsy research. We found that the transition to seizure is not a sudden phenomenon, but is instead a slow process that is characterized by the progressive loss of neuronal network resilience. From a dynamical perspective, the slow transition is governed by the principles of critical slowing, a robust natural phenomenon that is observable in systems characterized by transitions between dynamical regimes. In epilepsy, this process is modulated by synchronous synaptic input from IEDs. The IEDs are external perturbations that produce phasic changes in the slow transition process and exert opposing effects on the dynamics of a seizure-generating network, causing either antiseizure or proseizure effects. We found that the multifaceted nature of IEDs is defined by the dynamical state of the network at the moment of the discharge occurrence.

Biophysical Modeling Suggests Optimal Drug Combinations for Improving the Efficacy of GABA Agonists after Traumatic Brain Injuries.

Traumatic brain injuries (TBI) lead to dramatic changes in the surviving brain tissue. Altered ion concentrations, coupled with changes in the expression of membrane-spanning proteins, create a post-TBI brain state that can lead to further neuronal loss caused by secondary excitotoxicity. Several GABA receptor agonists have been tested in the search for neuroprotection immediately after an injury, with paradoxical results. These drugs not only fail to offer neuroprotection, but can also slow down functional recovery after TBI. Here, using computational modeling, we provide a biophysical hypothesis to explain these observations. We show that the accumulation of intracellular chloride ions caused by a transient upregulation of Na+-K+-2Cl- (NKCC1) co-transporters as observed following TBI, causes GABA receptor agonists to lead to excitation and depolarization block, rather than the expected hyperpolarization. The likelihood of prolonged, excitotoxic depolarization block is further exacerbated by the extremely high levels of extracellular potassium seen after TBI. Our modeling results predict that the neuroprotective efficacy of GABA receptor agonists can be substantially enhanced when they are combined with NKCC1 co-transporter inhibitors. This suggests a rational, biophysically principled method for identifying drug combinations for neuroprotection after TBI.

Quantitative simulation of extracellular single unit recording from the surface of cortex.

OBJECTIVE: Neural recording is important for a wide variety of clinical applications. Until recently, recording from the surface of the brain, even when using micro-electrocorticography (µECoG) arrays, was not thought to enable recording from individual neurons. Recent results suggest that when the surface electrode contact size is sufficiently small, it may be possible to record single neurons from the brain's surface. In this study, we use computational techniques to investigate the ability of surface electrodes to record the activity of single neurons. APPROACH: The computational model included the rat head, µECoG electrode, two existing multi-compartmental neuron models, and a novel multi-compartmental neuron model derived from patch clamp experiments in layer 1 of the cortex. MAIN RESULTS: Using these models, we reproduced single neuron recordings from µECoG arrays, and elucidated their possible source. The model resembles the experimental data when spikes originate from layer 1 neurons that are less than 60 µm from the cortical surface. We further used the model to explore the design space for surface electrodes. Although this model does not include biological or thermal noise, the results indicate the electrode contact area should be 100 µm2 or smaller to maintain a detectable waveform amplitude. Furthermore, the model shows the width of lateral insulation could be reduced, which may reduce scar formation, while retaining 95% of signal amplitude. SIGNIFICANCE: Overall, the model suggests single-unit surface recording is limited to neurons in layer 1 and further improvement in electrode design is needed.

Ictal and preictal power changes outside of the seizure focus correlate with seizure generalization.

OBJECTIVE: The treatment of focal epilepsies is largely predicated on the concept that there is a "focus" from which the seizure emanates. Yet, the physiological context that determines if and how ictal activity starts and propagates remains poorly understood. To delineate these phenomena more completely, we studied activity outside the seizure-onset zone prior to and during seizure initiation. METHODS: Stereotactic depth electrodes were implanted in 17 patients with longstanding pharmacoresistant epilepsy for lateralization and localization of the seizure-onset zone. Only seizures with focal onset in mesial temporal structures were used for analysis. Spectral analyses were used to quantify changes in delta, theta, alpha, beta, gamma, and high gamma frequency power, in regions inside and outside the area of seizure onset during both preictal and seizure initiation periods. RESULTS: In the 78 seizures examined, an average of 9.26% of the electrode contacts outside of the seizure focus demonstrated changes in power at seizure onset. Of interest, seizures that were secondarily generalized, on average, showed power changes in a greater number of extrafocus electrode contacts at seizure onset (16.7%) compared to seizures that remained focal (3.8%). The majority of these extrafocus changes occupied the delta and theta bands in electrodes placed in the ipsilateral, lateral temporal lobe. Preictally, we observed extrafocal high-frequency power decrements, which also correlated with seizure spread. SIGNIFICANCE: This widespread activity at and prior to the seizure-onset time further extends the notion of the ictogenic focus and its relationship to seizure spread. Further understanding of these extrafocus, periictal changes might help identify the neuronal dynamics underlying the initiation of seizures and how therapies can be devised to control seizure activity.