How vision and movement combine in the hippocampal place code

How do external environmental and internal movement-related information combine to tell us where we are? We examined the neural representation of environmental location provided by hippocampal place cells while mice navigated a virtual reality environment in which both types of information could be manipulated. Extracellular recordings were made from region CA1 of head-fixed mice navigating a virtual linear track and running in a similar real environment. Despite the absence of vestibular motion signals, normal place cell firing and theta rhythmicity were found. Visual information alone was sufficient for localized firing in 25% of place cells and to maintain a local field potential theta rhythm (but with significantly reduced power). Additional movement-related information was required for normally localized firing by the remaining 75% of place cells. Trials in which movement and visual information were put into conflict showed that they combined nonlinearly to control firing location, and that the relative influence of movement versus visual information varied widely across place cells. However, within this heterogeneity, the behavior of fully half of the place cells conformed to a model of path integration in which the presence of visual cues at the start of each run together with subsequent movement-related updating of position was sufficient to maintain normal fields.Hippocampal place cells fire when the animal visits a specific area in a familiar environment (1), providing a population representation of self-location (2–4). However, it is still unclear what information determines their firing location (“place field”). Existing models suggest that movement-related information updates the representation of self-location from moment-to-moment (i.e., performing “path integration”), whereas environmental information provides initial localization and allows the accumulating error inherent in path integration to be corrected sporadically (5–13). Previous experimental work addressing this question has found it difficult to dissociate the different types of information available in the real world. Both external sensory cues (3, 14–16) and internal self-motion information (17–19) can influence place cell firing, but these have usually been tightly coupled in previous experiments.To date, a range of computational models predicting place fields has been proposed based on the assumption that either environmental sensory information (20–22) or a self-motion metric is fundamental (7, 23). However, there is no agreement on which is more important and how these signals combine to generate spatially localized place cell firing and its temporal organization with respect to the theta rhythm (24). Recent studies showed that mice could navigate in a virtual environment (VE) and a small sample of place cells has been recorded in mice running on a virtual linear track (25–27). VE affords the opportunity to isolate the visual environment and internal movement-related information from other sensory information, and to study their contributions to place cell firing. Here we use manipulations of these inputs in a VE to dissociate the relative contributions to place cell firing and theta rhythmicity of external sensory information relating to the (virtual) visual environment and internal movement-related (motoric and proprioceptive) information.     

Behavioral response inhibition and maturation of goal representation in prefrontal cortex after puberty

Executive functions including behavioral response inhibition mature after puberty, in tandem with structural changes in the prefrontal cortex. Little is known about how activity of prefrontal neurons relates to this profound cognitive development. To examine this, we tracked neuronal responses of the prefrontal cortex in monkeys as they transitioned from puberty into adulthood and compared activity at different developmental stages. Performance of the antisaccade task greatly improved in this period. Among neural mechanisms that could facilitate it, reduction of stimulus-driven activity, increased saccadic activity, or enhanced representation of the opposing goal location, only the latter was evident in adulthood. Greatly accentuated in adults, this neural correlate of vector inversion may be a prerequisite to the formation of a motor plan to look away from the stimulus. Our results suggest that the prefrontal mechanisms that underlie mature performance on the antisaccade task are more strongly associated with forming an alternative plan of action than with suppressing the neural impact of the prepotent stimulus.Behavioral response inhibition, and cognitive task performance more generally, improves substantially between the time of puberty and adulthood (1–4). Risky decision-making peaks in adolescence, the time period between puberty and adulthood that is most closely linked to delinquent behavior in humans (5–7). Performance in tasks that assay response inhibition, such as the antisaccade task, improves into adulthood, reflecting the progressive development of behavioral control (3). This period of cognitive enhancement parallels the maturation of the prefrontal cortex (8–11). Anatomical changes in the prefrontal cortex continue during adolescence, involving gray and white matter volumes and myelination of axon fibers within the prefrontal cortex and between the prefrontal cortex and other areas (8–15). Changes in prefrontal activation, including increases (12, 16–20) and decreases (21, 22), have been documented in imaging studies for tasks that require inhibition of prepotent behavioral responses and filtering of distractors.Much less is known about how the physiological properties of prefrontal neurons develop after puberty. Similar to the human pattern of development, the monkey prefrontal cortex undergoes anatomical maturation in adolescence and early adulthood (23, 24). Male monkeys enter puberty at ∼3.5 y of age and reach full sexual maturity at 5 y, approximately equivalent to the human ages of 11 y and 16 y, respectively (25, 26). By some accounts, biochemical and anatomical changes characteristic of adolescence in humans occur at an earlier, prepubertal age in the monkey prefrontal cortex (27, 28), so it is not known if cognitive maturation or neurophysiological changes occur in monkeys after puberty. The contribution of prefrontal cortex to antisaccade performance has also been a matter of debate, with contrasting views favoring mechanisms of inhibiting movement toward the visual stimulus or enhancing movement away from it (29–31). Potential maturation of behavioral response inhibition may therefore be associated with a more efficient suppression of the stimulus representation in neural activity (weaker visual responses to stimuli inside the receptive field), stronger motor responses (higher activity to saccades), or enhancement of the appropriate goal representation (stronger activity for planning a saccade away from the stimulus). To examine the mechanisms that facilitate the mature ability to resist generating a response toward a salient stimulus, we used developmental markers to track transition from puberty to adulthood in monkeys and sought to identify neural correlates of changes in antisaccade performance within the visual and saccade-related activations of prefrontal neurons.     

Stimulus-dependent variability and noise correlations in cortical MT neurons

Population codes assume that neural systems represent sensory inputs through the firing rates of populations of differently tuned neurons. However, trial-by-trial variability and noise correlations are known to affect the information capacity of neural codes. Although recent studies have shown that stimulus presentation reduces both variability and rate correlations with respect to their spontaneous level, possibly improving the encoding accuracy, whether these second order statistics are tuned is unknown. If so, second-order statistics could themselves carry information, rather than being invariably detrimental. Here we show that rate variability and noise correlation vary systematically with stimulus direction in directionally selective middle temporal (MT) neurons, leading to characteristic tuning curves. We show that such tuning emerges in a stochastic recurrent network, for a set of connectivity parameters that overlaps with a single-state scenario and multistability. Information theoretic analysis shows that second-order statistics carry information that can improve the accuracy of the population code.Cortical activity is highly variable during spontaneous activity (1–4) and even when tested under constant experimental conditions (5–8). This variability is thought to limit the capacity of individual neurons to transmit information (9). Furthermore, variability is often correlated among neurons, and thus, it cannot be completely removed by averaging the population response (9–12). Recent experimental studies have examined the second-order statistics of neural responses across a variety of species, cortical areas, tasks, and stimulus and/or attentional conditions (13–17). In particular, it has been shown that the Fano factor (FF)—that is, the ratio between the variance of the spike counts over trials and its mean—is reduced when a stimulus is applied (16), thus improving the encoding of the stimulus. Importantly, both preferred and nonpreferred stimuli reduced the FF. In addition, the evoked noise correlation—that is, the trial-to-trial covariance of stimulus induced activity between two simultaneously recorded neurons—is also reduced upon stimulus presentation (18), after stimulus adaptation (19) or perceptual learning (20), and under attention (14, 21), an effect that could, under certain conditions, lead to more reliable estimates of the mean population activity (22). Hence, there is a growing body of evidence suggesting that the encoding of a signal through cortical activity may be improved by minimizing both trial-by-trial variability and noise correlations. However, it remains an open experimental and theoretical question, whether these statistics are themselves tuned to different stimulus features, an aspect that may be overlooked when only analyzing preferred and nonpreferred stimuli.Here, we examined the statistics of responses of area–middle temporal (MT) neurons in awake, fixating primates, to moving gratings and different plaid patterns of different directions, as well as moving gratings of different luminance contrasts. Specifically, we examined the baseline levels and the evoked directional and contrast tuning of the FF of individual neurons and the noise correlations between pairs of neurons with similar direction preferences. To get further theoretical insight, we investigated the effect of an applied stimulus on variability and correlations in an extended ring network model implementing direction selectivity (23).We found that both the trial-by-trial variability and the noise correlations among MT neurons showed a directional tuning that is not trivially explained by firing rate variations alone. We demonstrated that the tuning of these second-order statistics is well explained by a ring model operating near or beyond a bifurcation separating a single homogeneous state regime and a regime of multistability. Finally, we evaluated the impact of tuned second-order statistics on the accuracy of the population code.     

Local generation of multineuronal spike sequences in the hippocampal CA1 region

Sequential activity of multineuronal spiking can be observed during theta and high-frequency ripple oscillations in the hippocampal CA1 region and is linked to experience, but the mechanisms underlying such sequences are unknown. We compared multineuronal spiking during theta oscillations, spontaneous ripples, and focal optically induced high-frequency oscillations (“synthetic” ripples) in freely moving mice. Firing rates and rate modulations of individual neurons, and multineuronal sequences of pyramidal cell and interneuron spiking, were correlated during theta oscillations, spontaneous ripples, and synthetic ripples. Interneuron spiking was crucial for sequence consistency. These results suggest that participation of single neurons and their sequential order in population events are not strictly determined by extrinsic inputs but also influenced by local-circuit properties, including synapses between local neurons and single-neuron biophysics.A hypothesized hallmark of cognition is self-organized sequential activation of neuronal assemblies (1). Self-organized neuronal sequences have been observed in several cortical structures (2–5) and neuronal models (6–7). In the hippocampus, sequential activity of place cells (8) may be induced by external landmarks perceived by the animal during spatial navigation (9) and conveyed to CA1 by the upstream CA3 region or layer 3 of the entorhinal cortex (10). Internally generated sequences have been also described in CA1 during theta oscillations in memory tasks (4, 11), raising the possibility that a given neuronal substrate is responsible for generating sequences at multiple time scales. The extensive recurrent excitatory collateral system of the CA3 region has been postulated to be critical in this process (4, 7, 12, 13).The sequential activity of place cells is “replayed” during sharp waves (SPW) in a temporally compressed form compared with rate modulation of place cells (14–20) and may arise from the CA3 recurrent excitatory networks during immobility and slow wave sleep. The SPW-related convergent depolarization of CA1 neurons gives rise to a local, fast oscillatory event in the CA1 region (“ripple,” 140–180 Hz; refs. 8 and 21). Selective elimination of ripples during or after learning impairs memory performance (22–24), suggesting that SPW ripple-related replay assists memory consolidation (12, 13). Although the local origin of the ripple oscillations is well demonstrated (25, 26), it has been tacitly assumed that the ripple-associated, sequentially ordered firing of CA1 neurons is synaptically driven by the upstream CA3 cell assemblies (12, 15), largely because excitatory recurrent collaterals in the CA1 region are sparse (27). However, sequential activity may also emerge by local mechanisms, patterned by the different biophysical properties of CA1 pyramidal cells and their interactions with local interneurons, which discharge at different times during a ripple (28–30). A putative function of the rich variety of interneurons is temporal organization of principal cell spiking (29–32). We tested the “local-circuit” hypothesis by comparing the probability of participation and sequential firing of CA1 neurons during theta oscillations, natural spontaneous ripple events, and “synthetic” ripples induced by local optogenetic activation of pyramidal neurons.     

Self-assembly of alkynylplatinum(II) terpyridine amphiphiles into nanostructures via steric control and metal–metal interactions

A series of mono- and dinuclear alkynylplatinum(II) terpyridine complexes containing the hydrophilic oligo(para-phenylene ethynylene) with two 3,6,9-trioxadec-1-yloxy chains was designed and synthesized. The mononuclear alkynylplatinum(II) terpyridine complex was found to display a very strong tendency toward the formation of supramolecular structures. Interestingly, additional end-capping with another platinum(II) terpyridine moiety of various steric bulk at the terminal alkyne would lead to the formation of nanotubes or helical ribbons. These desirable nanostructures were found to be governed by the steric bulk on the platinum(II) terpyridine moieties, which modulates the directional metal−metal interactions and controls the formation of nanotubes or helical ribbons. Detailed analysis of temperature-dependent UV-visible absorption spectra of the nanostructured tubular aggregates also provided insights into the assembly mechanism and showed the role of metal−metal interactions in the cooperative supramolecular polymerization of the amphiphilic platinum(II) complexes.Square-planar d⁸ platinum(II) polypyridine complexes have long been known to exhibit intriguing spectroscopic and luminescence properties (1–54) as well as interesting solid-state polymorphism associated with metal−metal and π−π stacking interactions (1–14, 25). Earlier work by our group showed the first example, to our knowledge, of an alkynylplatinum(II) terpyridine system [Pt(tpy)(C ≡ CR)]⁺ that incorporates σ-donating and solubilizing alkynyl ligands together with the formation of Pt···Pt interactions to exhibit notable color changes and luminescence enhancements on solvent composition change (25) and polyelectrolyte addition (26). This approach has provided access to the alkynylplatinum(II) terpyridine and other related cyclometalated platinum(II) complexes, with functionalities that can self-assemble into metallogels (27–31), liquid crystals (32, 33), and other different molecular architectures, such as hairpin conformation (34), helices (35–38), nanostructures (39–45), and molecular tweezers (46, 47), as well as having a wide range of applications in molecular recognition (48–52), biomolecular labeling (48–52), and materials science (53, 54). Recently, metal-containing amphiphiles have also emerged as a building block for supramolecular architectures (42–44, 55–59). Their self-assembly has always been found to yield different molecular architectures with unprecedented complexity through the multiple noncovalent interactions on the introduction of external stimuli (42–44, 55–59).Helical architecture is one of the most exciting self-assembled morphologies because of the uniqueness for the functional and topological properties (60–69). Helical ribbons composed of amphiphiles, such as diacetylenic lipids, glutamates, and peptide-based amphiphiles, are often precursors for the growth of tubular structures on an increase in the width or the merging of the edges of ribbons (64, 65). Recently, the optimization of nanotube formation vs. helical nanostructures has aroused considerable interests and can be achieved through a fine interplay of the influence on the amphiphilic property of molecules (66), choice of counteranions (67, 68), or pH values of the media (69), which would govern the self-assembly of molecules into desirable aggregates of helical ribbons or nanotube scaffolds. However, a precise control of supramolecular morphology between helical ribbons and nanotubes remains challenging, particularly for the polycyclic aromatics in the field of molecular assembly (64–69). Oligo(para-phenylene ethynylene)s (OPEs) with solely π−π stacking interactions are well-recognized to self-assemble into supramolecular system of various nanostructures but rarely result in the formation of tubular scaffolds (70–73). In view of the rich photophysical properties of square-planar d⁸ platinum(II) systems and their propensity toward formation of directional Pt···Pt interactions in distinctive morphologies (27–31, 39–45), it is anticipated that such directional and noncovalent metal−metal interactions might be capable of directing or dictating molecular ordering and alignment to give desirable nanostructures of helical ribbons or nanotubes in a precise and controllable manner.Herein, we report the design and synthesis of mono- and dinuclear alkynylplatinum(II) terpyridine complexes containing hydrophilic OPEs with two 3,6,9-trioxadec-1-yloxy chains. The mononuclear alkynylplatinum(II) terpyridine complex with amphiphilic property is found to show a strong tendency toward the formation of supramolecular structures on diffusion of diethyl ether in dichloromethane or dimethyl sulfoxide (DMSO) solution. Interestingly, additional end-capping with another platinum(II) terpyridine moiety of various steric bulk at the terminal alkyne would result in nanotubes or helical ribbons in the self-assembly process. To the best of our knowledge, this finding represents the first example of the utilization of the steric bulk of the moieties, which modulates the formation of directional metal−metal interactions to precisely control the formation of nanotubes or helical ribbons in the self-assembly process. Application of the nucleation–elongation model into this assembly process by UV-visible (UV-vis) absorption spectroscopic studies has elucidated the nature of the molecular self-assembly, and more importantly, it has revealed the role of metal−metal interactions in the formation of these two types of nanostructures.     

Tectal microcircuit generating visual selection commands on gaze-controlling neurons

The optic tectum (called superior colliculus in mammals) is critical for eye–head gaze shifts as we navigate in the terrain and need to adapt our movements to the visual scene. The neuronal mechanisms underlying the tectal contribution to stimulus selection and gaze reorientation remains, however, unclear at the microcircuit level. To analyze this complex—yet phylogenetically conserved—sensorimotor system, we developed a novel in vitro preparation in the lamprey that maintains the eye and midbrain intact and allows for whole-cell recordings from prelabeled tectal gaze-controlling cells in the deep layer, while visual stimuli are delivered. We found that receptive field activation of these cells provide monosynaptic retinal excitation followed by local GABAergic inhibition (feedforward). The entire remaining retina, on the other hand, elicits only inhibition (surround inhibition). If two stimuli are delivered simultaneously, one inside and one outside the receptive field, the former excitatory response is suppressed. When local inhibition is pharmacologically blocked, the suppression induced by competing stimuli is canceled. We suggest that this rivalry between visual areas across the tectal map is triggered through long-range inhibitory tectal connections. Selection commands conveyed via gaze-controlling neurons in the optic tectum are, thus, formed through synaptic integration of local retinotopic excitation and global tectal inhibition. We anticipate that this mechanism not only exists in lamprey but is also conserved throughout vertebrate evolution.Visual scenes are composed of abundant stimuli, and the gaze needs continuously to be redirected toward different objects—an important task for the brain. Current models postulate that stimulus selection occurs through a process involving competitive interaction between different visual stimuli, resulting in the appropriate eye–head movement (1–5). The optic tectum (superior colliculus in mammals) has a causal role in the stimulus selection process (6–12) and not only in the control of saccades and eye–head gaze shifts (13–16). Although the collicular contribution to the selection process is of central importance, the underlying neuronal processes have remained elusive due to methodological limitations. It is our aim here to address this issue in a novel experimental model.The optic tectum is well developed in the lamprey, belonging to the oldest extant vertebrate group that evolved 560 million years ago (17), and it has remained conserved throughout vertebrate phylogeny (18–22). Afferents from retina provide a direct input to the superficial layers of the optic tectum, where a retinotopic map is formed (23–26). The intermediate and deep layers give rise to projections to brainstem areas and a motor map is formed that is responsible for the coordination of eye, head, and body movements (22, 27–29).To uncover the mechanisms underlying visual stimulus selection for gaze reorientation, detailed intracellular analysis is needed in combination with visual activation, which has not been possible in the classic mammalian preparations. To achieve this, we have developed a preparation in lamprey that maintains the eye and the midbrain intact in vitro, which has allowed us to perform whole-cell recordings from identified gaze-controlling cells in the optic tectum, while delivering natural and focal light stimuli within the visual field and monitoring and manipulating the synaptic responses. The retinotopic map in the lamprey tectum and the aligned motor map have been described in considerable detail (22, 26), and the lamprey nervous system from forebrain to spinal cord is experimentally very accessible, well described, and also conserved throughout vertebrate evolution (30–32).Although most mammalian studies have focused on the role of the retinotopic excitatory circuits that mediate signal transmission between the superficial layer and the deeper layers (33–36), only more recent studies have emphasized the role of GABAergic circuits in the collicular control of gaze (37–45). The question how collicular GABAergic systems affect stimulus selection for gaze motor action has, however, remained unanswered because most studies have relied on extracellular recordings in vivo and therefore have not allowed an analysis of the synaptic basis for these inhibitory interactions.We show here that tectal gaze-controlling cells receive intense excitatory monosynaptic retinal input in a bottom-up manner, which with a slight delay is followed by an even stronger inhibition from local GABAergic neurons. The local inhibition gives rise to visual stimulus selectivity by suppressing competing retinotopic stimuli with long-range horizontal projections across tectum. When this inhibition is blocked, stimulus selection is eliminated and gaze-controlling cells could discharge action potentials indiscriminately whether or not competing stimuli were present. The presence of a potential target will trigger local inhibitory and horizontally projecting neurons that will aim to reduce the excitability of cells in other tectal areas, hence, reducing the likelihood of executing a gaze motor response to other distracting stimuli. This stimulus suppression mechanism provides a robust solution for generating accurate attentional shifts, because the outcome of the synaptic interaction is directly integrated by the tectal output cells responsible for gaze action.     

Tonic GABAA conductance bidirectionally controls interneuron firing pattern and synchronization in the CA3 hippocampal network

The spiking output of interneurons is key for rhythm generation in the brain. However, what controls interneuronal firing remains incompletely understood. Here we combine dynamic clamp experiments with neural network simulations to understand how tonic GABA_A conductance regulates the firing pattern of CA3 interneurons. In baseline conditions, tonic GABA_A depolarizes these cells, thus exerting an excitatory action while also reducing the excitatory postsynaptic potential (EPSP) amplitude through shunting. As a result, the emergence of weak tonic GABA_A conductance transforms the interneuron firing pattern driven by individual EPSPs into a more regular spiking mode determined by the cell intrinsic properties. The increased regularity of spiking parallels stronger synchronization of the local network. With further increases in tonic GABA_A conductance the shunting inhibition starts to dominate over excitatory actions and thus moderates interneuronal firing. The remaining spikes tend to follow the timing of suprathreshold EPSPs and thus become less regular again. The latter parallels a weakening in network synchronization. Thus, our observations suggest that tonic GABA_A conductance can bidirectionally control brain rhythms through changes in the excitability of interneurons and in the temporal structure of their firing patterns.Rhythmic activity paces signal transfer within brain circuits. Brain rhythms are believed to depend heavily on the networks of inhibitory interneurons (1–4). In addition to synaptic inputs, interneuron excitability in the hippocampus is determined by tonic GABA_A conductance (5, 6), which could thus contribute to hippocampal rhythmogenesis. Indeed, GABA transaminase inhibitor vigabatrin increases the ambient GABA concentration, enhancing the power of the theta-rhythm in rats (7). In mice expressing GFP under the GAD67 promoter the reduced levels of ambient GABA correlate with a decreased power of kainate-induced oscillations in vitro (8). The latter decrease is reversed by a GABA uptake inhibitor, guvacine, which raises ambient GABA. GABA release by astrocytes also increases the gamma oscillation power in hippocampal area CA1 in vivo (9). Intriguingly, in hippocampal slices of animals lacking δ subunit-containing GABA_A receptors (which mediate tonic conductance in many local cell types including interneurons) the average frequency of cholinergically induced gamma oscillations is increased, whereas the oscillation power tends to drop (10). However, cellular mechanisms underlying such phenomena remain poorly understood.One possible explanation is the influence of tonic GABA_A conductance on the firing pattern of interneurons. Activation of GABA_A receptors inhibits most neurons, through either membrane hyperpolarization or shunting or both (11). In the adult brain, a depolarizing action of GABA has also been reported in various cell types, including hippocampal interneurons (3, 12–15). GABAergic depolarization can prompt spike generation, thus countering the shunting effects (14, 16). Therefore, experimental evidence indicates that the net effect of GABA_A receptor activation combines the excitatory action of depolarization and the inhibitory consequences of shunting, with the latter prevailing when the GABA_A receptor conductance is sufficiently strong. As a result, increasing the tonic GABA_A signaling can have a biphasic effect on individual hippocampal interneurons: excitatory at weak conductances and inhibitory at strong (14). Here we find that weak tonic GABA_A conductance favors a more regular firing pattern of interneurons, thus facilitating synchronization of the CA3 network. In contrast, strong GABA_A conductance makes the firing pattern more dependent on the stochastic excitatory synaptic input, thus reducing network synchrony.     

CRYPTOCHROME-mediated phototransduction by modulation of the potassium ion channel β-subunit redox sensor

Blue light activation of the photoreceptor CRYPTOCHROME (CRY) evokes rapid depolarization and increased action potential firing in a subset of circadian and arousal neurons in Drosophila melanogaster. Here we show that acute arousal behavioral responses to blue light significantly differ in mutants lacking CRY, as well as mutants with disrupted opsin-based phototransduction. Light-activated CRY couples to membrane depolarization via a well conserved redox sensor of the voltage-gated potassium (K⁺) channel β-subunit (Kvβ) Hyperkinetic (Hk). The neuronal light response is almost completely absent in hk^−/− mutants, but is functionally rescued by genetically targeted neuronal expression of WT Hk, but not by Hk point mutations that disable Hk redox sensor function. Multiple K⁺ channel α-subunits that coassemble with Hk, including Shaker, Ether-a-go-go, and Ether-a-go-go–related gene, are ion conducting channels for CRY/Hk-coupled light response. Light activation of CRY is transduced to membrane depolarization, increased firing rate, and acute behavioral responses by the Kvβ subunit redox sensor.CRYPTOCHROME (CRY) is a photoreceptor that mediates rapid membrane depolarization and increased spontaneous action potential firing rate in response to blue light in arousal and circadian neurons in Drosophila melanogaster (1, 2). CRY regulates circadian entrainment by targeting circadian clock proteins to proteasomal degradation in response to light (3–6). CRY is expressed in a small subset of central brain circadian, arousal, and photoreceptor neurons in D. melanogaster and other insects, including the large lateral ventral neuron (LNv; l-LNv) subset (1, 2, 7, 8). The l-LNvs are light-activated arousal neurons (1, 2, 9–11), whereas the small lateral ventral neurons (s-LNvs) are critical for circadian function (5, 12). Previous results suggest that light activated arousal is likely attenuated in cry-null mutants. In addition to modulating light-activated firing rate, membrane excitability in the LNv neurons helps maintain circadian rhythms (9, 13, 14), and LNv firing rate is circadian regulated (2, 16).Based on our previous work suggesting that l-LNv electrophysiological light response requires a flavin-specific redox reaction and modulation of membrane K⁺ channels, we investigated the molecular mechanism for CRY phototransduction to determine how light-activated CRY is coupled to rapid membrane electrical changes. Sequence and structural data suggest that the cytoplasmic Kvβs are redox sensors based on a highly conserved aldo-keto-reductase domain (AKR) (17–21). Although no functional role for redox sensing by Kvβ subunits has been established yet in vivo, studies with heterologously expressed WT and mutant Kvβ subunits show that they confer modulatory sensitivity to coexpressed K⁺ channels in response to oxidizing and reducing chemical agents (22–24). Mammals express six Kvβ genes, whereas Drosophila expresses a single Kvβ designated HYPERKINETIC (Hk) (18). We find that the light-activated redox reaction of the flavin adenine dinucleotide (FAD) chromophore in CRY has a distinct phototransduction mechanism that evokes membrane electrical responses via the Kvβ subunit Hk, which we show is a functional redox sensor in vivo.     

Therapeutic mechanisms of high-frequency stimulation in Parkinson’s disease and neural restoration via loop-based reinforcement

High-frequency deep brain stimulation (HFS) is clinically recognized to treat parkinsonian movement disorders, but its mechanisms remain elusive. Current hypotheses suggest that the therapeutic merit of HFS stems from increasing the regularity of the firing patterns in the basal ganglia (BG). Although this is consistent with experiments in humans and animal models of Parkinsonism, it is unclear how the pattern regularization would originate from HFS. To address this question, we built a computational model of the cortico-BG-thalamo-cortical loop in normal and parkinsonian conditions. We simulated the effects of subthalamic deep brain stimulation both proximally to the stimulation site and distally through orthodromic and antidromic mechanisms for several stimulation frequencies (20–180 Hz) and, correspondingly, we studied the evolution of the firing patterns in the loop. The model closely reproduced experimental evidence for each structure in the loop and showed that neither the proximal effects nor the distal effects individually account for the observed pattern changes, whereas the combined impact of these effects increases with the stimulation frequency and becomes significant for HFS. Perturbations evoked proximally and distally propagate along the loop, rendezvous in the striatum, and, for HFS, positively overlap (reinforcement), thus causing larger poststimulus activation and more regular patterns in striatum. Reinforcement is maximal for the clinically relevant 130-Hz stimulation and restores a more normal activity in the nuclei downstream. These results suggest that reinforcement may be pivotal to achieve pattern regularization and restore the neural activity in the nuclei downstream and may stem from frequency-selective resonant properties of the loop.High-frequency (i.e., above 100 Hz) deep brain stimulation (HFS) of the basal ganglia (BG) and thalamus is clinically recognized to treat movement disorders in Parkinson’s disease (PD) (1–4), but its therapeutic mechanisms remain unclear (5, 6).Early hypotheses about HFS were derived from the rate-based model of the BG function (7, 8) and postulated the disruption of the output of the BG-thalamic system via either the inactivation of neurons in the stimulated site (target) (9–15), which would provide an effect similar to a surgical lesion, or the abnormal excitation of axons projecting out of the target (16–19), which would disrupt the neuronal activity in the structures downstream, including any pathophysiological activity (20).More recently, an ever-growing number of experiments in PD humans and animal models of Parkinsonism has indicated that HFS affects the firing patterns of the neurons rather than the mean firing rate both in the target and the structures downstream (18, 19, 21–31) and it replaces repetitive low-frequency (i.e., ≤50 Hz) bursting patterns with regularized (i.e., more tonic) patterns at higher frequencies (25, 26). It has been proposed that increased pattern regularity of neurons in the target may be therapeutic (5, 32–37), but it is still unknown how this regularity comes about with HFS.It has been suggested that an increased pattern regularity can deplete the information content of the target output and this lack of information would act as an “information lesion” (33) and prevent the pathological activity from being transmitted within the BG-thalamic system (22, 33, 36). As a result, an information lesion in the target [typically, one among the subthalamic nucleus (STN), internal globus pallidus (GPi), or thalamus] would have effects similar to those of a destructive lesion in the same site, which has been reported to alleviate the movement disorders (38).Instead, studies (32, 34, 35, 37) have suggested that an increased pattern regularity of the BG output partly compensates the PD-evoked impairment of the information-processing capabilities of the thalamo-cortical system, and this restores a more faithful thalamic relay of the sensorimotor information (35, 39).Although intriguing, these hypotheses remain elusive on (i) the neuronal mechanisms that would elicit pattern regularization (e.g., why regularization would be relevant only for HFS) and (ii) the effects that increased regularity would have on the cortico-BG-thalamo-cortical loop.It has been hypothesized that pattern regularization occurs because axons projecting out of the target follow the pattern of the stimulus pulses (40, 41) and, given the segregated organization of the BG-thalamic connections (42), it has been assumed that pattern regularization percolates straightforward from the target to the structures immediately downstream (34, 36). However, this representation of the pattern regularization as a “local” effect can hardly be reconciled with the fact that HFS of any structure of the cortico-BG-thalamo-cortical loop is therapeutic for at least some movement disorders (1–4, 43–47), nor does it explain why stimulation at frequencies above 160–180 Hz is not necessarily therapeutic despite the fact that the regularity of the axonal patterns may increase (48, 49). Moreover, coherence in the 8–30-Hz band among neurons across different structures may decrease under HFS but not for lower frequencies (26, 50–52), which suggests the emergence of diffused changes in neuronal activity that would be hardly accounted for with purely local effects.There is emerging evidence, instead, that HFS affects multiple structures simultaneously. First, it has been shown that deep brain stimulation (DBS) may antidromically activate afferent axons and fibers of passage (53–59), thus reaching structures not immediately downstream. Second, studies (57, 58) observed in 6-hydroxydopamine (6-OHDA)-intoxicated rats that the antidromic effects increase with the stimulation frequency and peak around 110–130 Hz. Third, it has been shown in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-intoxicated nonhuman primates (NHPs) that STN DBS may evoke similar poststimulus responses in different BG structures, both downstream from and upstream to the STN (5, 27, 28, 30, 60). Finally, it has been reported that the cortico-BG-thalamo-cortical system consists of multiple sets of reentrant, interconnected, and partially overlapping neuronal loops (5, 42, 61, 62), which means that the structures upstream to the target (e.g., the striatum) may play an important role in the therapeutic mechanisms of HFS.Altogether, these results suggest that (A) pattern regularization is a global effect that exploits the closed-loop nature of the cortico-BG-thalamo-cortical system and selectively emerges only for specific HFS values, and that (B) the therapeutic merit of pattern regularization has to deal with the restoration of a more normal functionality of the entire cortico-BG-thalamo-cortical loop rather than with variations in the information content of one specific structure.We explored hypotheses (A) and (B) and assessed the system-wide effects of DBS by constructing a computational model of the cortico-BG-thalamo-cortical loop in both normal and parkinsonian conditions and by simulating the effects of STN DBS both at low (20–80 Hz) and high (100–180 Hz) frequencies. The model includes populations of single-compartment neurons and interneurons from motor cortex, striatum, GPi, and thalamus according to a network topology derived from the NHP anatomy, and it simulates both the orthodromic and antidromic effects of DBS. As a result, this model reproduced both average activity and discharge patterns of single units in NHP and rats under normal and parkinsonian conditions, with and without DBS, for all modeled structures.We show through numerical simulation that hypothesis (A) is significantly contributed by reinforcement mechanisms in the striatum. These mechanisms are selectively elicited by HFS, facilitate the percolation of regularized discharge patterns from the striatum to the GPi, and have a primary role in (B), because the percolated striato-pallidal input combines with the local effects of STN DBS to restore the thalamic relay function (63).     

Stochastic transitions into silence cause noise correlations in cortical circuits

The spiking activity of cortical neurons is highly variable. This variability is generally correlated among nearby neurons, an effect commonly interpreted to reflect the coactivation of neurons due to anatomically shared inputs. Recent findings, however, indicate that correlations can be dynamically modulated, suggesting that the underlying mechanisms are not well understood. Here, we investigate the hypothesis that correlations are dominated by neuronal coinactivation: the occurrence of brief silent periods during which all neurons in the local network stop firing. We recorded spiking activity from large populations of neurons in the auditory cortex of anesthetized rats across different brain states. During spontaneous activity, the reduction of correlation accompanying brain state desynchronization was largely explained by a decrease in the density of the silent periods. The presentation of a stimulus caused an initial drop of correlations followed by a rebound, a time course that was mimicked by the instantaneous silence density. We built a rate network model with fluctuation-driven transitions between a silent and an active attractor and assumed that neurons fired Poisson spike trains with a rate following the model dynamics. Variations of the network external input altered the transition rate into the silent attractor and reproduced the relation between correlation and silence density found in the data, both in spontaneous and evoked conditions. This suggests that the observed changes in correlation, occurring gradually with brain state variations or abruptly with sensory stimulation, are due to changes in the likeliness of the microcircuit to transiently cease firing.Neuronal noise correlations are defined as common fluctuations in the spiking activity of neurons under conditions of constant sensory input or motor output. Traditionally, they have been thought to arise from the dense connectivity of the cortex, such that neighboring neurons sharing a fraction of their inputs should also share a fraction of their output variability (1). Several observations are consistent with this hypothesis: pairwise correlations in the cortex decrease with cell pair distance (2) or with the difference in stimulus selectivity (3), dependencies that could follow from a variation in shared input given the anatomy of cortical circuits. Recent findings, however, challenge this simple interpretation. Recordings in the primate visual cortex have shown that attention or task context can change correlation structure (4–6) and that the magnitude of averaged correlation can be very low (7). In anesthetized rodents correlations decrease with brain state desynchronization (8, 9) or when animals switch from quiet wakefulness to active whisking during waking (10). Moreover, the commonly observed drop of spiking variability following stimulus onset (11–13) seems to occur jointly with a transient decrease in correlation (2, 14, 15). These observations suggest that correlations reflect the dynamical state of the circuit more than its hardwired connectivity.Despite substantial progress in understanding the mechanisms giving rise to large individual variability in recurrent networks (9, 16–18), we still lack a canonical model that can generate correlations with the same magnitude and spatiotemporal structure as those observed in cortical circuits. Balanced networks, for instance, a common model that reproduces the large variability of cortical neurons (9, 18, 19), show near-zero averaged correlations (9). Numerous studies have investigated the generation of synchronous firing (20), but whether short bursts of population activity can quantitatively account for the spike count correlations found in the data is unclear. Recurrent networks can also generate fast oscillations in the population activity, but, in a regime of low rates, typical of cortical circuits, average spike count correlations are negligible (21). Network models producing nonzero average correlations are those exhibiting up and down dynamics (22–29). Most of these studies have focused on investigating the mechanisms underlying the slow oscillatory activity observed in cortical slices (30), under anesthesia (31, 32), or during slow-wave sleep (33). Only recently the impact of up and down switching on trial-to-trial response variability (25) and on the probability distribution of multiunit activity (29) across brain states has been investigated. Whether the alternation between up and down phases could quantitatively account for the pairwise correlations observed in different brain states and describe their stimulus-evoked dynamics remains an open question.To investigate the mechanisms producing correlated firing, we recorded the spiking activity of large populations of neurons from the auditory cortex of anesthetized rats. During spontaneous activity, changes in correlation were largely explained by variation of the occurrence rate of periods during which neurons in the circuit stopped firing. Furthermore, the time course of correlation in response to an acoustic stimulus reflected the transient variation of this silence density. A computational rate model with fluctuation-driven transitions between silent and active attractors could explain the experimentally observed time course of correlation and its relation to silence density. Our findings suggest that the dynamics of these transitions play a fundamental role in generating noise correlations among cortical neurons.     

Electrical synapses connect a network of gonadotropin releasing hormone neurons in a cichlid fish

Initiating and regulating vertebrate reproduction requires pulsatile release of gonadotropin-releasing hormone (GnRH1) from the hypothalamus. Coordinated GnRH1 release, not simply elevated absolute levels, effects the release of pituitary gonadotropins that drive steroid production in the gonads. However, the mechanisms underlying synchronization of GnRH1 neurons are unknown. Control of synchronicity by gap junctions between GnRH1 neurons has been proposed but not previously found. We recorded simultaneously from pairs of transgenically labeled GnRH1 neurons in adult male Astatotilapia burtoni cichlid fish. We report that GnRH1 neurons are strongly and uniformly interconnected by electrical synapses that can drive spiking in connected cells and can be reversibly blocked by meclofenamic acid. Our results suggest that electrical synapses could promote coordinated spike firing in a cellular assemblage of GnRH1 neurons to produce the pulsatile output necessary for activation of the pituitary and reproduction.Development and function of the reproductive system in vertebrates depends on the timing and levels of signaling by gonadal sex steroids (1, 2). Production of these steroids is controlled by neurons expressing gonadotropin-releasing hormone (GnRH1), which comprise the final output of the brain to the hypothalamic-pituitary-gonadal axis. During vertebrate development, GnRH1 neurons originate outside the central nervous system in the olfactory placode and migrate into the basal forebrain (3–6). These neurons signal to the pituitary via the decapeptide GnRH1 to effect the release of the gonadotropins, follicle stimulating hormone and luteinizing hormone, which in turn stimulate steroid production by the gonads. It has long been known that this release depends on coordinated, pulsatile GnRH1 release, not simply elevated levels (7, 8), requiring some level of synchronization in the output of these neurons. Episodic activation of the pituitary gonadotropes has been observed in multiple vertebrate taxa, including mammals and fish (9–12), however, mechanisms that underlie this required coordinated activity of GnRH1 neurons are unknown. Synchrony could in principle derive from coincident input from a “pacemaker” neural population, from direct coupling of GnRH1 neurons, or from a combination of mechanisms. Gap junction-mediated coupling has been suspected to play a role, as synchronous firing can be observed in neurons mechanically isolated from brain slices and in cultures of embryonic mouse and primate neurons, and immortalized mouse GnRH1 neurons express the connexin proteins that constitute gap junctions (13–15). However, no evidence for gap junctions among adult GnRH1 cells in vivo has been found (16, 17).To search for the origin of synchrony among these neurons, we used a unique model system for analysis of GnRH1 neurons, Astatotilapia burtoni, a cichlid fish. GnRH1 neurons in males of this species exhibit dynamic morphological plasticity caused by changes in their social status (18–21). Here we use transgenic dominant male A. burtoni to perform paired recordings from GnRH1 neurons, and report that they are reciprocally connected by electrical synapses. These findings suggest that gap junctions contribute to the coordinated firing of these neurons necessary for reproductive function.     

Structural interactions of a voltage sensor toxin with lipid membranes

Protein toxins from tarantula venom alter the activity of diverse ion channel proteins, including voltage, stretch, and ligand-activated cation channels. Although tarantula toxins have been shown to partition into membranes, and the membrane is thought to play an important role in their activity, the structural interactions between these toxins and lipid membranes are poorly understood. Here, we use solid-state NMR and neutron diffraction to investigate the interactions between a voltage sensor toxin (VSTx1) and lipid membranes, with the goal of localizing the toxin in the membrane and determining its influence on membrane structure. Our results demonstrate that VSTx1 localizes to the headgroup region of lipid membranes and produces a thinning of the bilayer. The toxin orients such that many basic residues are in the aqueous phase, all three Trp residues adopt interfacial positions, and several hydrophobic residues are within the membrane interior. One remarkable feature of this preferred orientation is that the surface of the toxin that mediates binding to voltage sensors is ideally positioned within the lipid bilayer to favor complex formation between the toxin and the voltage sensor.Protein toxins from venomous organisms have been invaluable tools for studying the ion channel proteins they target. For example, in the case of voltage-activated potassium (Kv) channels, pore-blocking scorpion toxins were used to identify the pore-forming region of the channel (1, 2), and gating modifier tarantula toxins that bind to S1–S4 voltage-sensing domains have helped to identify structural motifs that move at the protein–lipid interface (3–5). In many instances, these toxin–channel interactions are highly specific, allowing them to be used in target validation and drug development (6–8).Tarantula toxins are a particularly interesting class of protein toxins that have been found to target all three families of voltage-activated cation channels (3, 9–12), stretch-activated cation channels (13–15), as well as ligand-gated ion channels as diverse as acid-sensing ion channels (ASIC) (16–21) and transient receptor potential (TRP) channels (22, 23). The tarantula toxins targeting these ion channels belong to the inhibitor cystine knot (ICK) family of venom toxins that are stabilized by three disulfide bonds at the core of the molecule (16, 17, 24–31). Although conventional tarantula toxins vary in length from 30 to 40 aa and contain one ICK motif, the recently discovered double-knot toxin (DkTx) that specifically targets TRPV1 channels contains two separable lobes, each containing its own ICK motif (22, 23).One unifying feature of all tarantula toxins studied thus far is that they act on ion channels by modifying the gating properties of the channel. The best studied of these are the tarantula toxins targeting voltage-activated cation channels, where the toxins bind to the S3b–S4 voltage sensor paddle motif (5, 32–36), a helix-turn-helix motif within S1–S4 voltage-sensing domains that moves in response to changes in membrane voltage (37–41). Toxins binding to S3b–S4 motifs can influence voltage sensor activation, opening and closing of the pore, or the process of inactivation (4, 5, 36, 42–46). The tarantula toxin PcTx1 can promote opening of ASIC channels at neutral pH (16, 18), and DkTx opens TRPV1 in the absence of other stimuli (22, 23), suggesting that these toxin stabilize open states of their target channels.For many of these tarantula toxins, the lipid membrane plays a key role in the mechanism of inhibition. Strong membrane partitioning has been demonstrated for a range of toxins targeting S1–S4 domains in voltage-activated channels (27, 44, 47–50), and for GsMTx4 (14, 50), a tarantula toxin that inhibits opening of stretch-activated cation channels in astrocytes, as well as the cloned stretch-activated Piezo1 channel (13, 15). In experiments on stretch-activated channels, both the d- and l-enantiomers of GsMTx4 are active (14, 50), implying that the toxin may not bind directly to the channel. In addition, both forms of the toxin alter the conductance and lifetimes of gramicidin channels (14), suggesting that the toxin inhibits stretch-activated channels by perturbing the interface between the membrane and the channel. In the case of Kv channels, the S1–S4 domains are embedded in the lipid bilayer and interact intimately with lipids (48, 51, 52) and modification in the lipid composition can dramatically alter gating of the channel (48, 53–56). In one study on the gating of the Kv2.1/Kv1.2 paddle chimera (53), the tarantula toxin VSTx1 was proposed to inhibit Kv channels by modifying the forces acting between the channel and the membrane. Although these studies implicate a key role for the membrane in the activity of Kv and stretch-activated channels, and for the action of tarantula toxins, the influence of the toxin on membrane structure and dynamics have not been directly examined. The goal of the present study was to localize a tarantula toxin in membranes using structural approaches and to investigate the influence of the toxin on the structure of the lipid bilayer.     

Melanopsin-driven increases in maintained activity enhance thalamic visual response reliability across a simulated dawn

Twice a day, at dawn and dusk, we experience gradual but very high amplitude changes in background light intensity (irradiance). Although we perceive the associated change in environmental brightness, the representation of such very slow alterations in irradiance by the early visual system has been little studied. Here, we addressed this deficit by recording electrophysiological activity in the mouse dorsal lateral geniculate nucleus under exposure to a simulated dawn. As irradiance increased we found a widespread enhancement in baseline firing that extended to units with ON as well as OFF responses to fast luminance increments. This change in baseline firing was equally apparent when the slow irradiance ramp appeared alone or when a variety of higher-frequency artificial or natural visual stimuli were superimposed upon it. Using a combination of conventional knockout, chemogenetic, and receptor-silent substitution manipulations, we continued to show that, over higher irradiances, this increase in firing originates with inner-retinal melanopsin photoreception. At the single-unit level, irradiance-dependent increases in baseline firing were strongly correlated with improvements in the amplitude of responses to higher-frequency visual stimuli. This in turn results in an up to threefold increase in single-trial reliability of fast visual responses. In this way, our data indicate that melanopsin drives a generalized increase in dorsal lateral geniculate nucleus excitability as dawn progresses that both conveys information about changing background light intensity and increases the signal:noise for fast visual responses.The rotation of the earth imposes slow but very high amplitude changes in background light intensity (irradiance) across dawn and dusk. An array of light adaptation mechanisms acts to buffer the visual code against this substantial variation in its physical origins (1–8). Nonetheless, we certainly perceive the change in brightness of our environment, raising the question of how the visual system represents such gradual changes in irradiance.The question of how the early visual system encodes background light levels has previously been addressed by extended exposure to spatially uniform stimuli. Under these conditions, many neurons in the retina and visual thalamus scale their maintained firing rate according to stimulus irradiance over many decades (9–14). This behavior, sometimes termed “luxotonic,” implies that natural slow changes in irradiance would be represented by gradual modulations in firing rate across at least a fraction of the visual projection. However, we are unaware of a direct test of that prediction. Moreover, the extent to which luxotonic activity survives in the presence of higher-frequency visual stimuli (as would be the case in any natural scene) remains unknown. We start here by addressing these deficits and showing that naturalistic dawn transitions do indeed induce a diffuse increase in firing across the mouse dorsal lateral geniculate nucleus (dLGN).Although the luxotonic capacity of the mammalian visual system has been appreciated for >50 y, both the retinal origins and functional significance of this mode of action remain controversial. An important question is how luxotonic changes in maintained firing impact the ability of neurons to encode other visual features. There is the obvious potential for increases in baseline firing to occlude other responses; it has also been suggested that luxotonic behavior could improve signal:noise for fast visual responses by regularizing firing patterns (9, 15; although see refs. 16 and 17). A second aim of this study was to resolve this controversy, by directly measuring responses to high-frequency visual stimuli across naturalistic ramps in irradiance.Our final objective was to address the retinal circuitry responsible for luxotonic activity. Under mesopic and photopic conditions, cone photoreceptors track fast modulations in local luminance, with rapid alterations in membrane potential. However, they also can encode background light intensity with changes in steady-state voltage, and this signal can be propagated through the retinal circuitry to support luxotonic activity in ganglion cells and beyond (18–21). At brighter backgrounds, however, the photoreceptor steady state response approaches saturation (6, 22, 23). Under these conditions, further changes in maintained firing could be driven by intrinsically photosensitive retinal ganglion cells (ipRGCs), which can rely upon their intrinsic melanopsin-dependent light response to accurately encode higher irradiances (24). Here we used a combination of conventional knockout, receptor-silent substitution and chemogenetic manipulations to test the hypothesis that ipRGCs support responses to naturalistic changes in irradiance under these conditions.     

Thalamocortical rhythms during a vibrotactile detection task

To explore the role of oscillatory dynamics of the somatosensory thalamocortical network in perception and decision making, we recorded the simultaneous neuronal activity in the ventral posterolateral nucleus (VPL) of the somatosensory thalamus and primary somatosensory cortex (S1) in two macaque monkeys performing a vibrotactile detection task. Actively detecting a vibrotactile stimulus and reporting its perception elicited a sustained poststimulus beta power increase in VPL and an alpha power decrease in S1, in both stimulus-present and stimulus-absent trials. These oscillatory dynamics in the somatosensory thalamocortical network depended on the behavioral context: they were stronger for the active detection condition than for a passive stimulation condition. Furthermore, contrasting stimulus-present vs. stimulus-absent responses, we found that poststimulus theta power increased in both VPL and S1, and alpha/beta power decreased in S1, reflecting the monkey’s perceptual decision but not the motor response per se. Additionally, higher prestimulus alpha power in S1 correlated with an increased probability of the monkey reporting a stimulus, regardless of the actual presence of a stimulus. Thus, we found task-related modulations in oscillatory activity, not only in the neocortex but also in the thalamus, depending on behavioral context. Furthermore, oscillatory modulations reflected the perceptual decision process and subsequent behavioral response. We conclude that these early sensory regions, in addition to their primary sensory functions, may be actively involved in perceptual decision making.Presenting a subject with a (weak) sensory stimulus sometimes leads to perception and sometimes not. What exactly determines the detection of a stimulus has been a central question in the study of sensory perception (1). The neural correlates of somatosensory perceptual detection have been studied extensively in both human and nonhuman primates (2–6). Spike recordings in nonhuman primates showed the contribution of a distributed network of sensorimotor regions to somatosensory decision making, including primary and secondary somatosensory cortices and prefrontal, premotor, and motor areas (7, 8). It was suggested that the neuronal correlates of subjective sensory perception progressively build up as information traverses the cortical circuits, gradually transforming the encoded sensory information into a perceptual decision (5, 9). Crucially, a spike firing rate reflecting the decision process has been detected in secondary somatosensory cortex (S2) and frontal areas, but not in the primary somatosensory cortex (S1) (8, 9).Previous work focused mainly on the role of the sensorimotor cortex, whereas only a few studies explored the role of the somatosensory thalamus. Most thalamic recordings have been either in tissue slices (10, 11) or in anesthetized animals (12, 13). With only a few studies in awake, behaving animals (14, 15), the thalamic contribution to somatosensory detection performance remained largely unknown. We recently conducted an experiment in which we recorded the simultaneous neuronal activity across the ventral posterolateral nucleus (VPL) and S1 in two monkeys (Macaca mulatta) performing a vibrotactile detection task (6, 16). These recordings of single-unit activity in VPL of awake, behaving monkeys showed that neural activity in these nuclei reflects stimulus properties but not the animal’s percept (6). Similarly, studies in the lateral geniculate nucleus (LGN), the visual equivalent of VPL, found that spike activity reflects retinal input rather than subjective perception (17, 18). Nevertheless, a study in which spikes were recorded in monkey LGN, showed an enhanced response to attended stimuli compared with nonattended stimuli (19).Although these studies focusing on single-unit spikes led to many important insights, additional understanding of perceptual decision processes may be gained by studying neuronal population dynamics as reflected by the local field potential (LFP). Several studies in humans (using EEG/magnetoencephalography) showed that cortical oscillatory dynamics influence somatosensory detection performance by setting the state of the brain networks involved (20, 21). Importantly, these studies showed that fluctuations in (anticipatory) prestimulus activity in early sensory areas, predominantly in the alpha (8–14 Hz) and beta bands (15–30 Hz), modulate the likelihood of subsequent stimulus detection (2–4, 22–26).Here, we report on the oscillatory dynamics in the somatosensory thalamocortical network. We studied LFPs that were recorded concurrently in the aforementioned detection experiments (6, 16) and asked how oscillatory activity contributes to perceptual decision making. To assess the context dependency of stimulus processing, we compared active stimulus detection with a passive control condition. This was done by investigating oscillatory activity in the LFPs of VPL and S1 and by exploring the influence of the observed oscillatory dynamics on task performance.     

Predictive Value of Brain Natriuretic Peptides in Patients on Peritoneal Dialysis: Results from the ADEMEX Trial

Background and objectives: Natriuretic peptides have been suggested to be of value in risk stratification in dialysis patients. Data in patients on peritoneal dialysis remain limited.Design, setting, participants, & measurements: Patients of the ADEMEX trial (ADEquacy of peritoneal dialysis in MEXico) were randomized to a control group [standard 4 × 2L continuous ambulatory peritoneal dialysis (CAPD); n = 484] and an intervention group (CAPD with a target creatinine clearance ≥60L/wk/1.73 m²; n = 481). Natriuretic peptides were measured at baseline and correlated with other parameters as well as evaluated for effects on patient outcomes.Results: Control group and intervention group were comparable at baseline with respect to all measured parameters. Baseline values of natriuretic peptides were elevated and correlated significantly with levels of residual renal function but not with body size or diabetes. Baseline values of N-terminal fragment of B-type natriuretic peptide (NT-proBNP) but not proANP(1–30), proANP(31–67), or proANP(1–98) were independently highly predictive of overall survival and cardiovascular mortality. Volume removal was also significantly correlated with patient survival.Conclusions. NT-proBNP have a significant predictive value for survival of CAPD patients and may be of value in guiding risk stratification and potentially targeted therapeutic interventions.Plasma levels of cardiac natriuretic peptides are elevated in patients with chronic kidney disease, owing to impairment of renal function, hypertension, hypervolemia, and/or concomitant heart disease (1–7). Atrial natriuretic peptide (ANP) and particularly brain natriuretic peptide (BNP) levels are linked independently to left ventricular mass (3–5,8–16) and function (3,6–17) and predict total and cardiovascular mortality (1,3,8,10,12,18) as well as cardiac events (12,19). ANP and BNP decrease significantly during hemodialysis treatment but increase again during the interdialytic interval (1,2,4,6,7,14,17,20–23). Levels in patients on peritoneal dialysis (PD) have been found to be lower than in patients on hemodialysis (11,24–26), but the correlations with left ventricular function and structure are maintained in both types of dialysis modalities (11,15,27,28).The high mortality of patients on peritoneal dialysis and the failure of dialytic interventions to alter this mortality (29,30) necessitate renewed attention into novel methods of stratification and identification of patients at highest risk to be targeted for specific interventions. Cardiac natriuretic peptides are increasingly considered to fulfill this role in nonrenal patients. Evaluations of cardiac natriuretic peptides in patients on PD have been limited by small numbers (3,9,11,12,15,24–26) and only one study examined correlations between natriuretic peptide levels and outcomes (12). The PD population enrolled in the ADEMEX trial offered us the opportunity to evaluate cardiac natriuretic peptides and their value in predicting outcomes in the largest clinical trial ever performed on PD (29,30). It is hoped that such an evaluation would identify patients at risk even in the absence of overt clinical disease and hence facilitate or encourage interventions with salutary outcomes.     

Noradrenergic blockade stabilizes prefrontal activity and enables fear extinction under stress

Stress-induced impairments in extinction learning are believed to sustain posttraumatic stress disorder (PTSD). Noradrenergic signaling may contribute to extinction impairments by modulating medial prefrontal cortex (mPFC) circuits involved in fear regulation. Here we demonstrate that aversive fear conditioning rapidly and persistently alters spontaneous single-unit activity in the prelimbic and infralimbic subdivisions of the mPFC in behaving rats. These conditioning-induced changes in mPFC firing were mitigated by systemic administration of propranolol (10 mg/kg, i.p.), a β-noradrenergic receptor antagonist. Moreover, propranolol administration dampened the stress-induced impairment in extinction observed when extinction training is delivered shortly after fear conditioning. These findings suggest that β-adrenoceptors mediate stress-induced changes in mPFC spike firing that contribute to extinction impairments. Propranolol may be a helpful adjunct to behavioral therapy for PTSD, particularly in patients who have recently experienced trauma.Individuals exposed to extreme psychological stress, such as combat-related trauma or sexual abuse, are at risk for developing anxiety and trauma disorders, including posttraumatic stress disorder (PTSD). Although the etiology of PTSD is complex, it is widely believed that associative learning processes, including Pavlovian fear conditioning, contribute to its genesis. Moreover, an inability to suppress or extinguish fear memories may sustain pathologically high levels of fear in patients with PTSD years after the trauma (1–6). A variety of clinical interventions to facilitate fear extinction in patients with PTSD are currently being explored, although effective treatment for many afflicted individuals remains elusive (7, 8).One promising therapeutic target for facilitating extinction in PTSD patients is the noradrenergic system. Norepinephrine (NE) not only plays an important role in mood and arousal, but also in the encoding, retrieval, and reconsolidation of emotional memories (9–13). Endogenous NE signaling is elevated in PTSD and drugs that block NE receptors are already being used with some success to either prevent or treat PTSD, including its symptoms of hyperarousal and nightmares (14–18). Clinically effective noradrenergic drugs include the α1-adrenoceptor antagonist, prazosin, and the β1/β2-adrenoceptor antagonist, propranolol (17, 19–21). The neural mechanisms underlying the efficacy of these drugs remain poorly understood.It has previously been suggested that stress-induced changes in prefrontal cortical structure and function observed in animal models may contribute to the extinction deficits observed in patients with PTSD (22–24). Given the abundant literature implicating NE signaling in prefrontal cortical function (25, 26), it is conceivable that stress-induced elevations in prefrontal NE release (27–29) contribute to extinction impairments associated with PTSD. The medial prefrontal cortex (mPFC), comprising the prelimbic (PL) and infralimbic (IL) subdivisions in rodents, plays a key role in the regulation of emotional behavior in both humans and rats (30, 31). Previous studies have suggested that PL plays an important role in fear expression, whereas IL is preferentially involved in fear extinction (32–34). Stress-induced alterations in the balance of neuronal activity in PL and IL as a consequence of noradrenergic hyperarousal might therefore contribute to extinction impairments and the maintenance of PTSD. To address this question, we combine in vivo microelectrode recording in freely moving rats with behavioral and pharmacological manipulations to determine whether β-noradrenergic receptors mediate stress-induced alterations in mPFC neuronal activity. Further, we examine whether systemic propranolol treatment, given immediately after an aversive experience, rescues stress-induced impairments in fear extinction.     

From the Cover: Why the proportion of transmission during early-stage HIV infection does not predict the long-term impact of treatment on HIV incidence

Antiretroviral therapy (ART) reduces the infectiousness of HIV-infected persons, but only after testing, linkage to care, and successful viral suppression. Thus, a large proportion of HIV transmission during a period of high infectiousness in the first few months after infection (“early transmission”) is perceived as a threat to the impact of HIV “treatment-as-prevention” strategies. We created a mathematical model of a heterosexual HIV epidemic to investigate how the proportion of early transmission affects the impact of ART on reducing HIV incidence. The model includes stages of HIV infection, flexible sexual mixing, and changes in risk behavior over the epidemic. The model was calibrated to HIV prevalence data from South Africa using a Bayesian framework. Immediately after ART was introduced, more early transmission was associated with a smaller reduction in HIV incidence rate—consistent with the concern that a large amount of early transmission reduces the impact of treatment on incidence. However, the proportion of early transmission was not strongly related to the long-term reduction in incidence. This was because more early transmission resulted in a shorter generation time, in which case lower values for the basic reproductive number (R₀) are consistent with observed epidemic growth, and R₀ was negatively correlated with long-term intervention impact. The fraction of early transmission depends on biological factors, behavioral patterns, and epidemic stage and alone does not predict long-term intervention impacts. However, early transmission may be an important determinant in the outcome of short-term trials and evaluation of programs.Recent studies have confirmed that effective antiretroviral therapy (ART) reduces the transmission of HIV among stable heterosexual couples (1–3). This finding has generated interest in understanding the population-level impact of HIV treatment on reducing the rate of new HIV infections in generalized epidemic settings (4). Research, including mathematical modeling (5–10), implementation research (11), and major randomized controlled trials (12–14), are focused on how ART provision might be expanded strategically to maximize its public health benefits (15, 16).One concern is that if a large fraction of HIV transmission occurs shortly after a person becomes infected, before the person can be diagnosed and initiated on ART, this will limit the potential impact of HIV treatment on reducing HIV incidence (9, 17, 18). Data suggest that persons are more infectious during a short period of “early infection” after becoming infected with HIV (19–22), although there is debate about the extent, duration, and determinants of elevated infectiousness (18, 23). The amount of transmission that occurs also will depend on patterns of sexual behavior and sexual networks (17, 24–27). There have been estimates for the contribution of early infection to transmission from mathematical models (7, 17, 21, 24–26) and phylogenetic analyses (28–31), but these vary widely, from 5% to above 50% (23).In this study, we use a mathematical model to quantify how the proportion of transmission that comes from persons who have been infected recently affects the impact of treatment scale-up on HIV incidence. The model is calibrated to longitudinal HIV prevalence data from South Africa using a Bayesian framework. Thus, the model accounts for not only the early epidemic growth rate highlighted in previous research (5, 9, 18), but also the heterogeneity and sexual behavior change to explain the peak and decline in HIV incidence observed in sub-Saharan African HIV epidemics (32, 33).The model calibration allows uncertainty about factors that determine the amount of early transmission, including the relative infectiousness during early infection, heterogeneity in propensity for sexual risk behavior, assortativity in sexual partner selection, reduction in risk propensity over the life course, and population-wide reductions in risk behavior in response to the epidemic (32, 33). This results in multiple combinations of parameter values that are consistent with the observed epidemic and variation in the amount of early transmission. We simulated the impact of a treatment intervention and report how the proportion of early transmission correlates with the reduction in HIV incidence from the intervention over the short- and long-term.