Natural patterns of activity and long-term synaptic plasticity

Theta Burst Stimulation of the Human Motor Cortex Modulates Secondary Hyperalgesia to Punctate Mechanical Stimuli

OBJECTIVES

Many chronic pain conditions show evidence of dysregulated synaptic plasticity, including the development and maintenance of central sensitization. This provides a strong rationale for neuromodulation therapies for the relief of chronic pain. However, variability in responses and low fidelity across studies remain an issue for both clinical trials and pain management, demonstrating insufficient mechanistic understanding of effective treatment protocols.

MATERIALS AND METHODS

In a randomized counterbalanced crossover designed study, we evaluated two forms of patterned repetitive transcranial magnetic stimulation, known as continuous theta burst stimulation (TBS) and intermittent TBS, during normal and central sensitization states. Secondary hyperalgesia (a form of use-dependent central sensitization) was induced using a well-established injury-free pain model and assessed by standardized quantitative sensory testing involving light touch and pinprick pain thresholds in addition to stimulus-response functions.

RESULTS

We found that continuous TBS of the human motor cortex has a facilitatory (pronociceptive) effect on the magnitude of perceived pain to secondary hyperalgesia, which may rely on induction and expression of neural plasticity through heterosynaptic long-term potentiation-like mechanisms.

CONCLUSIONS

By defining the underlying mechanisms of TBS-driven synaptic plasticity in the nociceptive system, we offer new insight into disease mechanisms and provide targets for promoting functional recovery and repair in chronic pain. For clinical applications, this knowledge is critical for development of more efficacious and mechanisms-based neuromodulation protocols, which are urgently needed to address the chronic pain and opioid epidemics.

Modeling Instantaneous Firing Rate of Deep Brain Stimulation Target Neuronal Ensembles in the Basal Ganglia and Thalamus

OBJECTIVE

Deep brain stimulation (DBS) is an effective treatment for movement disorders, including Parkinson disease and essential tremor. However, the underlying mechanisms of DBS remain elusive. Despite the capability of existing models in interpreting experimental data qualitatively, there are very few unified computational models that quantitatively capture the dynamics of the neuronal activity of varying stimulated nuclei-including subthalamic nucleus (STN), substantia nigra pars reticulata (SNr), and ventral intermediate nucleus (Vim)-across different DBS frequencies.

MATERIALS AND METHODS

Both synthetic and experimental data were used in the model fitting; the synthetic data were generated by an established spiking neuron model that was reported in our previous work, and the experimental data were provided using single-unit microelectrode recordings (MERs) during DBS (microelectrode stimulation). Based on these data, we developed a novel mathematical model to represent the firing rate of neurons receiving DBS, including neurons in STN, SNr, and Vim-across different DBS frequencies. In our model, the DBS pulses were filtered through a synapse model and a nonlinear transfer function to formulate the firing rate variability. For each DBS-targeted nucleus, we fitted a single set of optimal model parameters consistent across varying DBS frequencies.

RESULTS

Our model accurately reproduced the firing rates observed and calculated from both synthetic and experimental data. The optimal model parameters were consistent across different DBS frequencies.

CONCLUSIONS

The result of our model fitting was in agreement with experimental single-unit MER data during DBS. Reproducing neuronal firing rates of different nuclei of the basal ganglia and thalamus during DBS can be helpful to further understand the mechanisms of DBS and to potentially optimize stimulation parameters based on their actual effects on neuronal activity.

Synaptic plasticity through a naturalistic lens

From the myriad of studies on neuronal plasticity, investigating its underlying molecular mechanisms up to its behavioral relevance, a very complex landscape has emerged. Recent efforts have been achieved toward more naturalistic investigations as an attempt to better capture the synaptic plasticity underpinning of learning and memory, which has been fostered by the development of in vivo electrophysiological and imaging tools. In this review, we examine these naturalistic investigations, by devoting a first part to synaptic plasticity rules issued from naturalistic in vivo-like activity patterns. We next give an overview of the novel tools, which enable an increased spatio-temporal specificity for detecting and manipulating plasticity expressed at individual spines up to neuronal circuit level during behavior. Finally, we put particular emphasis on works considering brain-body communication loops and macroscale contributors to synaptic plasticity, such as body internal states and brain energy metabolism.

The Memristive Properties and Spike Timing-Dependent Plasticity in Electrodeposited Copper Tungstates and Molybdates

Memristors possess non-volatile memory, adjusting their electrical resistance to the current that flows through them and allowing switching between high and low conducting states. This technology could find applications in fields such as IT, consumer electronics, computing, sensors, and medicine. In this paper, we report successful electrodeposition of thin-film materials consisting of copper tungstate and copper molybdate (CuWO4 and Cu3Mo2O9), which showed notable memristive properties. Material characterisation was performed with techniques such as XRD, XPS, and SEM. The electrodeposited materials exhibited the ability to switch between low and high resistive states during varied cyclic scans and short-term impulses. The retention time of these switched states was also explored. Using these materials, the effects seen in biological systems, specifically spike timing-dependent plasticity, were simulated, being based on analogue operation of the memristors to achieve multiple conductivity states. Bio-inspired simulations performed directly on the material could possibly offer energy and time savings for classical computations. Memristors could be crucial for the advancement of high-efficiency, low-energy neuromorphic electronic devices and technologies in the future.

Brain IGF-I regulates LTP, spatial memory, and sexual dimorphic behavior

Insulin-like growth factor-I (IGF-I) exerts multiple actions, yet the role of IGF-I from different sources is poorly understood. Here, we explored the functional and behavioral consequences of the conditional deletion of Igf-I in the nervous system (Igf-I Δ/Δ), and demonstrated that long-term potentiation was impaired in hippocampal slices. Moreover, Igf-I Δ/Δ mice showed spatial memory deficits in the Morris water maze, and the significant sex-dependent differences displayed by Igf-I Ctrl/Ctrl mice disappeared in Igf-I Δ/Δ mice in the open field and rota-rod tests. Brain Igf-I deletion disorganized the granule cell layer of the dentate gyrus (DG), and it modified the relative expressions of GAD and VGLUT1, which are preferentially localized to inhibitory and excitatory presynaptic terminals. Furthermore, Igf-I deletion altered protein modules involved in receptor trafficking, synaptic proteins, and proteins that functionally interact with estrogen and androgen metabolism. Our findings indicate that brain IGF-I is crucial for long-term potentiation, and that it is involved in the regulation of spatial memory and sexual dimorphic behaviors, possibly by maintaining the granule cell layer structure and the stability of synaptic-related protein modules.

Homosynaptic plasticity induction causes heterosynaptic changes at the unstimulated neighbors in an induction pattern and location-specific manner

Dendritic spines are highly dynamic structures whose structural and functional fluctuations depend on multiple factors. Changes in synaptic strength are not limited to synapses directly involved in specific activity patterns. Unstimulated clusters of neighboring spines in and around the site of stimulation can also undergo alterations in strength. Usually, when plasticity is induced at single dendritic spines with glutamate uncaging, neighboring spines do not show any significant structural fluctuations. Here, using two-photon imaging and glutamate uncaging at single dendritic spines of hippocampal pyramidal neurons, we show that structural modifications at unstimulated neighboring spines occur and are a function of the temporal pattern of the plasticity-inducing stimulus. Further, the relative location of the unstimulated neighbors within the local dendritic segment correlates with the extent of heterosynaptic plasticity that is observed. These findings indicate that naturalistic patterns of activity at single spines can shape plasticity at nearby clusters of synapses, and may play a role in priming local inputs for further modifications.

Linking temporal coordination of hippocampal activity to memory function

Oscillations in neural activity are widespread throughout the brain and can be observed at the population level through the local field potential. These rhythmic patterns are associated with cycles of excitability and are thought to coordinate networks of neurons, in turn facilitating effective communication both within local circuits and across brain regions. In the hippocampus, theta rhythms (4-12 Hz) could contribute to several key physiological mechanisms including long-range synchrony, plasticity, and at the behavioral scale, support memory encoding and retrieval. While neurons in the hippocampus appear to be temporally coordinated by theta oscillations, they also tend to fire in sequences that are developmentally preconfigured. Although loss of theta rhythmicity impairs memory, these sequences of spatiotemporal representations persist in conditions of altered hippocampal oscillations. The focus of this review is to disentangle the relative contribution of hippocampal oscillations from single-neuron activity in learning and memory. We first review cellular, anatomical, and physiological mechanisms underlying the generation and maintenance of hippocampal rhythms and how they contribute to memory function. We propose candidate hypotheses for how septohippocampal oscillations could support memory function while not contributing directly to hippocampal sequences. In particular, we explore how theta rhythms could coordinate the integration of upstream signals in the hippocampus to form future decisions, the relevance of such integration to downstream regions, as well as setting the stage for behavioral timescale synaptic plasticity. Finally, we leverage stimulation-based treatment in Alzheimer's disease conditions as an opportunity to assess the sufficiency of hippocampal oscillations for memory function.

The temporal pattern of synaptic activation determines the longevity of structural plasticity at dendritic spines

Learning is thought to involve physiological and structural changes at individual synapses. Synaptic plasticity has predominantly been studied using regular stimulation patterns, but neuronal activity in the brain normally follows a Poisson distribution. We used two-photon imaging and glutamate uncaging to investigate the structural plasticity of single dendritic spines using naturalistic activation patterns sampled from a Poisson distribution. We showed that naturalistic activation patterns elicit structural plasticity that is both NMDAR and protein synthesis-dependent. Furthermore, we uncovered that the longevity of structural plasticity is dependent on the temporal structure of the naturalistic pattern. Finally, we found that during the delivery of the naturalistic activity, spines underwent rapid structural growth that predicted the longevity of plasticity. This was not observed with regularly spaced activity. These data reveal that different temporal organizations of the same number of synaptic stimulations can produce rather distinct short and long-lasting structural plasticity.

Advances in the Electrophysiological Recordings of Long-Term Potentiation

Understanding neuronal firing patterns and long-term potentiation (LTP) induction in studying learning, memory, and neurological diseases is critical. However, recently, despite the rapid advancement in neuroscience, we are still constrained by the experimental design, detection tools for exploring the mechanisms and pathways involved in LTP induction, and detection ability of neuronal action potentiation signals. This review will reiterate LTP-related electrophysiological recordings in the mammalian brain for nearly 50 years and explain how excitatory and inhibitory neural LTP results have been detected and described by field- and single-cell potentials, respectively. Furthermore, we focus on describing the classic model of LTP of inhibition and discuss the inhibitory neuron activity when excitatory neurons are activated to induce LTP. Finally, we propose recording excitatory and inhibitory neurons under the same experimental conditions by combining various electrophysiological technologies and novel design suggestions for future research. We discussed different types of synaptic plasticity, and the potential of astrocytes to induce LTP also deserves to be explored in the future.

Meta-learning biologically plausible plasticity rules with random feedback pathways

Backpropagation is widely used to train artificial neural networks, but its relationship to synaptic plasticity in the brain is unknown. Some biological models of backpropagation rely on feedback projections that are symmetric with feedforward connections, but experiments do not corroborate the existence of such symmetric backward connectivity. Random feedback alignment offers an alternative model in which errors are propagated backward through fixed, random backward connections. This approach successfully trains shallow models, but learns slowly and does not perform well with deeper models or online learning. In this study, we develop a meta-learning approach to discover interpretable, biologically plausible plasticity rules that improve online learning performance with fixed random feedback connections. The resulting plasticity rules show improved online training of deep models in the low data regime. Our results highlight the potential of meta-learning to discover effective, interpretable learning rules satisfying biological constraints.

Neural Field Continuum Limits and the Structure–Function Partitioning of Cognitive–Emotional Brain Networks

In The cognitive-emotional brain, Pessoa overlooks continuum effects on nonlinear brain network connectivity by eschewing neural field theories and physiologically derived constructs representative of neuronal plasticity. The absence of this content, which is so very important for understanding the dynamic structure-function embedding and partitioning of brains, diminishes the rich competitive and cooperative nature of neural networks and trivializes Pessoa’s arguments, and similar arguments by other authors, on the phylogenetic and operational significance of an optimally integrated brain filled with variable-strength neural connections. Riemannian neuromanifolds, containing limit-imposing metaplastic Hebbian- and antiHebbian-type control variables, simulate scalable network behavior that is difficult to capture from the simpler graph-theoretic analysis preferred by Pessoa and other neuroscientists. Field theories suggest the partitioning and performance benefits of embedded cognitive-emotional networks that optimally evolve between exotic classical and quantum computational phases, where matrix singularities and condensations produce degenerate structure-function homogeneities unrealistic of healthy brains. Some network partitioning, as opposed to unconstrained embeddedness, is thus required for effective execution of cognitive-emotional network functions and, in our new era of neuroscience, should be considered a critical aspect of proper brain organization and operation.

Quadriceps Weakness is Associated with Neuroplastic Changes Within Specific Corticospinal Pathways and Brain Areas After Anterior Cruciate Ligament Reconstruction: Theoretical Utility of Motor Imagery-Based Brain-Computer Interface Technology for Rehabilitation

Persistent quadriceps weakness is a problematic sequela of anterior cruciate ligament reconstruction (ACLR). The purposes of this review are to summarize neuroplastic changes after ACL reconstruction; provide an overview of a promising interventions, motor imagery (MI), and its utility in muscle activation; and propose a framework using a brain-computer interface (BCI) to augment quadriceps activation. A literature review of neuroplastic changes, MI training, and BCI-MI technology in postoperative neuromuscular rehabilitation was conducted in PubMed, Embase, and Scopus. Combinations of the following search terms were used to identify articles: "quadriceps muscle," "neurofeedback," "biofeedback," "muscle activation," "motor learning," "anterior cruciate ligament," and "cortical plasticity." We found that ACLR disrupts sensory input from the quadriceps, which results in reduced sensitivity to electrochemical neuronal signals, an increase in central inhibition of neurons regulating quadriceps control and dampening of reflexive motor activity. MI training consists of visualizing an action, without physically engaging in muscle activity. Imagined motor output during MI training increases the sensitivity and conductivity of corticospinal tracts emerging from the primary motor cortex, which helps "exercise" the connections between the brain and target muscle tissues. Motor rehabilitation studies using BCI-MI technology have demonstrated increased excitability of the motor cortex, corticospinal tract, spinal motor neurons, and disinhibition of inhibitory interneurons. This technology has been validated and successfully applied in the recovery of atrophied neuromuscular pathways in stroke patients but has yet to be investigated in peripheral neuromuscular insults, such as ACL injury and reconstruction. Well-designed clinical studies may assess the impact of BCI on clinical outcomes and recovery time. Quadriceps weakness is associated with neuroplastic changes within specific corticospinal pathways and brain areas. BCI-MI shows strong potential for facilitating recovery of atrophied neuromuscular pathways after ACLR and may offer an innovative, multidisciplinary approach to orthopaedic care.

Level of Evidence

V, expert opinion.

IGF-1 receptor regulates upward firing rate homeostasis via the mitochondrial calcium uniporter

An emerging hypothesis is that neuronal circuits homeostatically maintain a stable spike rate despite continuous environmental changes. This firing rate homeostasis is believed to confer resilience to neurodegeneration and cognitive decline. We show that insulin-like growth factor-1 receptor (IGF-1R) is necessary for homeostatic response of mean firing rate to inactivity, termed “upward firing rate homeostasis.” We show that its mechanism of action is to couple spike bursts with downstream mitochondrial Ca²⁺ influx via the mitochondrial calcium uniporter complex (MCUc). We propose that MCUc is a homeostatic Ca²⁺ sensor that triggers the integrated homeostatic response. Firing rate homeostasis may be the principal mechanism by which IGF-1R regulates aging and neurodevelopmental and neurodegenerative disorders.

Regulation of firing rate homeostasis constitutes a fundamental property of central neural circuits. While intracellular Ca²⁺ has long been hypothesized to be a feedback control signal, the molecular machinery enabling a network-wide homeostatic response remains largely unknown. We show that deletion of insulin-like growth factor-1 receptor (IGF-1R) limits firing rate homeostasis in response to inactivity, without altering the distribution of baseline firing rates. The deficient firing rate homeostatic response was due to disruption of both postsynaptic and intrinsic plasticity. At the cellular level, we detected a fraction of IGF-1Rs in mitochondria, colocalized with the mitochondrial calcium uniporter complex (MCUc). IGF-1R deletion suppressed transcription of the MCUc members and burst-evoked mitochondrial Ca²⁺ (mitoCa²⁺) by weakening mitochondria-to-cytosol Ca²⁺ coupling. Overexpression of either mitochondria-targeted IGF-1R or MCUc in IGF-1R–deficient neurons was sufficient to rescue the deficits in burst-to-mitoCa²⁺ coupling and firing rate homeostasis. Our findings indicate that mitochondrial IGF-1R is a key regulator of the integrated homeostatic response by tuning the reliability of burst transfer by MCUc. Based on these results, we propose that MCUc acts as a homeostatic Ca²⁺ sensor. Faulty activation of MCUc may drive dysregulation of firing rate homeostasis in aging and in brain disorders associated with aberrant IGF-1R/MCUc signaling.

Excitatory-inhibitory balance modulates the formation and dynamics of neuronal assemblies in cortical networks

Repetitive activation of subpopulations of neurons leads to the formation of neuronal assemblies, which can guide learning and behavior. Recent technological advances have made the artificial induction of these assemblies feasible, yet how various parameters of induction can be optimized is not clear. Here, we studied this question in large-scale cortical network models with excitatory-inhibitory balance. We found that the background network in which assemblies are embedded can strongly modulate their dynamics and formation. Networks with dominant excitatory interactions enabled a fast formation of assemblies, but this was accompanied by recruitment of other non-perturbed neurons, leading to some degree of nonspecific induction. On the other hand, networks with strong excitatory-inhibitory interactions ensured that the formation of assemblies remained constrained to the perturbed neurons, but slowed down the induction. Our results suggest that these two regimes can be suitable for computational and cognitive tasks with different trade-offs between speed and specificity.

Neuromodulated Dopamine Plastic Networks for Heterogeneous Transfer Learning with Hebbian Principle

The plastic modifications in synaptic connectivity is primarily from changes triggered by neuromodulated dopamine signals. These activities are controlled by neuromodulation, which is itself under the control of the brain. The subjective brain’s self-modifying abilities play an essential role in learning and adaptation. The artificial neural networks with neuromodulated plasticity are used to implement transfer learning in the image classification domain. In particular, this has application in image detection, image segmentation, and transfer of learning parameters with significant results. This paper proposes a novel approach to enhance transfer learning accuracy in a heterogeneous source and target, using the neuromodulation of the Hebbian learning principle, called NDHTL (Neuromodulated Dopamine Hebbian Transfer Learning). Neuromodulation of plasticity offers a powerful new technique with applications in training neural networks implementing asymmetric backpropagation using Hebbian principles in transfer learning motivated CNNs (Convolutional neural networks). Biologically motivated concomitant learning, where connected brain cells activate positively, enhances the synaptic connection strength between the network neurons. Using the NDHTL algorithm, the percentage of change of the plasticity between the neurons of the CNN layer is directly managed by the dopamine signal’s value. The discriminative nature of transfer learning fits well with the technique. The learned model’s connection weights must adapt to unseen target datasets with the least cost and effort in transfer learning. Using distinctive learning principles such as dopamine Hebbian learning in transfer learning for asymmetric gradient weights update is a novel approach. The paper emphasizes the NDHTL algorithmic technique as synaptic plasticity controlled by dopamine signals in transfer learning to classify images using source-target datasets. The standard transfer learning using gradient backpropagation is a symmetric framework. Experimental results using CIFAR-10 and CIFAR-100 datasets show that the proposed NDHTL algorithm can enhance transfer learning efficiency compared to existing methods.

Optogenetically Controlled Activity Pattern Determines Survival Rate of Developing Neocortical Neurons

A substantial proportion of neurons undergoes programmed cell death (apoptosis) during early development. This process is attenuated by increased levels of neuronal activity and enhanced by suppression of activity. To uncover whether the mere level of activity or also the temporal structure of electrical activity affects neuronal death rates, we optogenetically controlled spontaneous activity of synaptically-isolated neurons in developing cortical cultures. Our results demonstrate that action potential firing of primary cortical neurons promotes neuronal survival throughout development. Chronic patterned optogenetic stimulation allowed to effectively modulate the firing pattern of single neurons in the absence of synaptic inputs while maintaining stable overall activity levels. Replacing the burst firing pattern with a non-physiological, single pulse pattern significantly increased cell death rates as compared to physiological burst stimulation. Furthermore, physiological burst stimulation led to an elevated peak in intracellular calcium and an increase in the expression level of classical activity-dependent targets but also decreased Bax/BCL-2 expression ratio and reduced caspase 3/7 activity. In summary, these results demonstrate at the single-cell level that the temporal pattern of action potentials is critical for neuronal survival versus cell death fate during cortical development, besides the pro-survival effect of action potential firing per se.

Unsupervised changes in core object recognition behavior are predicted by neural plasticity in inferior temporal cortex

Temporal continuity of object identity is a feature of natural visual input and is potentially exploited - in an unsupervised manner - by the ventral visual stream to build the neural representation in inferior temporal (IT) cortex. Here, we investigated whether plasticity of individual IT neurons underlies human core object recognition behavioral changes induced with unsupervised visual experience. We built a single-neuron plasticity model combined with a previously established IT population-to-recognition-behavior-linking model to predict human learning effects. We found that our model, after constrained by neurophysiological data, largely predicted the mean direction, magnitude, and time course of human performance changes. We also found a previously unreported dependency of the observed human performance change on the initial task difficulty. This result adds support to the hypothesis that tolerant core object recognition in human and non-human primates is instructed - at least in part - by naturally occurring unsupervised temporal contiguity experience.

Burst-dependent synaptic plasticity can coordinate learning in hierarchical circuits

Synaptic plasticity is believed to be a key physiological mechanism for learning. It is well established that it depends on pre- and postsynaptic activity. However, models that rely solely on pre- and postsynaptic activity for synaptic changes have, so far, not been able to account for learning complex tasks that demand credit assignment in hierarchical networks. Here we show that if synaptic plasticity is regulated by high-frequency bursts of spikes, then pyramidal neurons higher in a hierarchical circuit can coordinate the plasticity of lower-level connections. Using simulations and mathematical analyses, we demonstrate that, when paired with short-term synaptic dynamics, regenerative activity in the apical dendrites and synaptic plasticity in feedback pathways, a burst-dependent learning rule can solve challenging tasks that require deep network architectures. Our results demonstrate that well-known properties of dendrites, synapses and synaptic plasticity are sufficient to enable sophisticated learning in hierarchical circuits.

How Negative Experience Influences the Brain: A Comprehensive Review of the Neurobiological Underpinnings of Nocebo Hyperalgesia

This comprehensive review summarizes and interprets the neurobiological correlates of nocebo hyperalgesia in healthy humans. Nocebo hyperalgesia refers to increased pain sensitivity resulting from negative experiences and is thought to be an important variable influencing the experience of pain in healthy and patient populations. The young nocebo field has employed various methods to unravel the complex neurobiology of this phenomenon and has yielded diverse results. To comprehend and utilize current knowledge, an up-to-date, complete review of this literature is necessary. PubMed and PsychInfo databases were searched to identify studies examining nocebo hyperalgesia while utilizing neurobiological measures. The final selection included 22 articles. Electrophysiological findings pointed toward the involvement of cognitive-affective processes, e.g., modulation of alpha and gamma oscillatory activity and P2 component. Findings were not consistent on whether anxiety-related biochemicals such as cortisol plays a role in nocebo hyperalgesia but showed an involvement of the cyclooxygenase-prostaglandin pathway, endogenous opioids, and dopamine. Structural and functional neuroimaging findings demonstrated that nocebo hyperalgesia amplified pain signals in the spinal cord and brain regions involved in sensory and cognitive-affective processing including the prefrontal cortex, insula, amygdala, and hippocampus. These findings are an important step toward identifying the neurobiological mechanisms through which nocebo effects may exacerbate pain. Results from the studies reviewed are discussed in relation to cognitive-affective and physiological processes involved in nocebo and pain. One major limitation arising from this review is the inconsistency in methods and results in the nocebo field. Yet, while current findings are diverse and lack replication, methodological differences are able to inform our understanding of the results. We provide insights into the complexities and involvement of neurobiological processes in nocebo hyperalgesia and call for more consistency and replication studies. By summarizing and interpreting the challenging and complex neurobiological nocebo studies this review contributes, not only to our understanding of the mechanisms through which nocebo effects exacerbate pain, but also to our understanding of current shortcomings in this field of neurobiological research.

The role of the anterior nuclei of the thalamus in human memory processing

Extensive neuroanatomical connectivity between the anterior thalamic nuclei (ATN) and hippocampus and neocortex renders them well-placed for a role in memory processing, and animal, lesion, and neuroimaging studies support such a notion. The deep location and small size of the ATN have precluded their real-time electrophysiological investigation during human memory processing. However, ATN electrophysiological recordings from patients receiving electrodes implanted for deep brain stimulation for pharmacoresistant focal epilepsy have enabled high temporal resolution study of ATN activity. Theta frequency synchronization of ATN and neocortical oscillations during successful memory encoding, enhanced phase alignment, and coupling between ATN local gamma frequency activity and frontal neocortical and ATN theta oscillations provide evidence of an active role for the ATN in memory encoding, potentially integrating information from widespread neocortical sources. Greater coupling of a broader gamma frequency range with theta oscillations at rest than during memory encoding provides additional support for the hypothesis that the ATN play a role in selecting local, task-relevant high frequency activity associated with particular features of a memory trace.

The Differences in the Whole-Brain Functional Network between Cantonese-Mandarin Bilinguals and Mandarin Monolinguals

Cantonese-Mandarin bilinguals are logographic-logographic bilinguals that provide a unique population for bilingual studies. Whole brain functional connectivity analysis makes up for the deficiencies of previous bilingual studies on the seed-based approach and helps give a complete picture of the brain connectivity profiles of logographic-logographic bilinguals. The current study is to explore the effect of the long-term logographic-logographic bilingual experience on the functional connectivity of the whole-brain network. Thirty Cantonese-Mandarin bilingual and 30 Mandarin monolingual college students were recruited in the study. Resting state functional magnetic resonance imaging (rs-fMRI) was performed to investigate the whole-brain functional connectivity differences by network-based statistics (NBS), and the differences in network efficiency were investigated by graph theory between the two groups (false discovery rate corrected for multiple comparisons, q = 0.05). Compared with the Mandarin monolingual group, Cantonese-Mandarin bilinguals increased functional connectivity between the bilateral frontoparietal and temporal regions and decreased functional connectivity in the bilateral occipital cortex and between the right sensorimotor region and bilateral prefrontal cortex. No significant differences in network efficiency were found between the two groups. Compared with the Mandarin monolinguals, Cantonese-Mandarin bilinguals had no significant discrepancies in network efficiency. However, the Cantonese-Mandarin bilinguals developed a more strongly connected subnetwork related to language control, inhibition, phonological and semantic processing, and memory retrieval, whereas a weaker connected subnetwork related to visual and phonology processing, and speech production also developed.

Muscarinic Regulation of Spike Timing Dependent Synaptic Plasticity in the Hippocampus

Long-term changes in synaptic transmission between neurons in the brain are considered the cellular basis of learning and memory. Over the last few decades, many studies have revealed that the precise order and timing of activity between pre- and post-synaptic cells ("spike-timing-dependent plasticity; STDP") is crucial for the sign and magnitude of long-term changes at many central synapses. Acetylcholine (ACh) via the recruitment of diverse muscarinic receptors is known to influence STDP in a variety of ways, enabling flexibility and adaptability in brain network activity during complex behaviors. In this review, we will summarize and discuss different mechanistic aspects of muscarinic modulation of timing-dependent plasticity at both excitatory and inhibitory synapses in the hippocampus to shape learning and memory.

Lithium chloride enhances serotonin induced calcium activity in EGFP-GnIH neurons

Neurons synthesizing gonadotropin-inhibitory hormone (GnIH) have been implicated in the control of reproduction, food intake and stress. Serotonin (5-HT) receptors have been shown in GnIH neurons; however, their functional role in the regulation of GnIH neurons remains to be elucidated. In this study, we measured intracellular calcium ion levels following 5-HT treatment to hypothalamic primary cultures of enhanced fluorescent green protein-tagged GnIH (EGFP-GnIH) neurons from Wistar rat pups of mixed sex. Three days after initial seeding of the primary cultures, the test groups were pre-treated with lithium chloride to selectively inhibit glycogen synthase kinase 3 beta to promote intracellular calcium levels, whereas the control groups received culture medium with no lithium chloride treatment. 24 h later, the cultures were incubated with rhodamine-2AM (rhod-2AM) calcium indicator dye for one hour prior to imaging. 5-HT was added to the culture dishes 5 min after commencement of imaging. Analysis of intracellular calcium levels in EGFP-GnIH neurons showed that pre-treatment with lithium chloride before 5-HT treatment resulted in significant increase in intracellular calcium levels, two times higher than the baseline. This suggests that lithium chloride enhances the responsiveness of GnIH neurons to 5-HT.

Activation of nicotinic acetylcholine receptors induces potentiation and synchronization within in vitro hippocampal networks

Nicotinic acetylcholine receptors (nAChRs) are known to play a role in cognitive functions of the hippocampus, such as memory consolidation. Given that they conduct Ca²⁺ and are capable of regulating the release of glutamate and γ-aminobutyric acid (GABA) within the hippocampus, thereby shifting the excitatory-inhibitory ratio, we hypothesized that the activation of nAChRs will result in the potentiation of hippocampal networks and alter synchronization. We used nicotine as a tool to investigate the impact of activation of nAChRs on neuronal network dynamics in primary embryonic rat hippocampal cultures prepared from timed-pregnant Sprague-Dawley rats. We perturbed cultured hippocampal networks with increasing concentrations of bath-applied nicotine and performed network extracellular recordings of action potentials using a microelectrode array. We found that nicotine modulated network dynamics in a concentration-dependent manner; it enhanced firing of action potentials as well as facilitated bursting activity. In addition, we used pharmacological agents to determine the contributions of discrete nAChR subtypes to the observed network dynamics. We found that β4-containing nAChRs are necessary for the observed increases in spiking, bursting, and synchrony, while the activation of α7 nAChRs augments nicotine-mediated network potentiation but is not necessary for its manifestation. We also observed that antagonists of N-methyl-D-aspartate receptors (NMDARs) and group I metabotropic glutamate receptors (mGluRs) partially blocked the effects of nicotine. Furthermore, nicotine exposure promoted autophosphorylation of Ca²⁺ /calmodulin-dependent kinase II (CaMKII) and serine 831 phosphorylation of the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) subunit GluA1. These results suggest that nicotinic receptors induce potentiation and synchronization of hippocampal networks and glutamatergic synaptic transmission. Findings from this work highlight the impact of cholinergic signaling in generating network-wide potentiation in the form of enhanced spiking and bursting dynamics that coincide with molecular correlates of memory such as increased phosphorylation of CaMKII and GluA1. OPEN SCIENCE BADGES: This article has received a badge for *Open Materials* because it provided all relevant information to reproduce the study in the manuscript. More information about the Open Practices badges can be found at https://cos.io/our-services/open-science-badges/.

Neuromodulators and Long-Term Synaptic Plasticity in Learning and Memory: A Steered-Glutamatergic Perspective

The molecular pathways underlying the induction and maintenance of long-term synaptic plasticity have been extensively investigated revealing various mechanisms by which neurons control their synaptic strength. The dynamic nature of neuronal connections combined with plasticity-mediated long-lasting structural and functional alterations provide valuable insights into neuronal encoding processes as molecular substrates of not only learning and memory but potentially other sensory, motor and behavioural functions that reflect previous experience. However, one key element receiving little attention in the study of synaptic plasticity is the role of neuromodulators, which are known to orchestrate neuronal activity on brain-wide, network and synaptic scales. We aim to review current evidence on the mechanisms by which certain modulators, namely dopamine, acetylcholine, noradrenaline and serotonin, control synaptic plasticity induction through corresponding metabotropic receptors in a pathway-specific manner. Lastly, we propose that neuromodulators control plasticity outcomes through steering glutamatergic transmission, thereby gating its induction and maintenance.

Insulin Modulates Excitatory Synaptic Transmission and Synaptic Plasticity in the Mouse Hippocampus

The administration of exogenous insulin into the hippocampus has the potential to enhance cognitive function and exert other beneficial effects. Elucidating the neurobiological substrates of insulin action and its underlying physiological mechanisms may further improve treatment efficacy. Previous work has shown that insulin affects synaptic plasticity, however there are discrepancies and contradictory conclusions between studies. Here, we used extracellular field recordings in mouse hippocampal slices to investigate how insulin acutely modulates synaptic transmission and synaptic plasticity, both of which are correlated with learning and memory processes. Our data demonstrate that insulin application inhibited basal excitatory synaptic transmission and promoted long-term potentiation (LTP) induction at hippocampal Schaffer collateral-CA1 synapses. Under similar conditions, insulin strongly activated the PI3K/AKT pathway, but had only a weak effect on the MAPK/ERK pathway. Although insulin-induced inhibition of field excitatory post-synaptic potentials (fEPSPs) was previously termed insulin-long-term depression (insulin-LTD), insulin application potentiated recovery from classically induced LTD. Further analysis suggests suppression of presynaptic neurotransmitter release contributed to the insulin-LTD. At low concentrations, insulin primarily inhibited fEPSPs; however, at high concentration, its effects were of mixed inhibition and enhancement in different recordings. Moreover, a broad spectrum protein kinase C blocker, cannabinoid receptor type 1 activator, or a high glucose concentration inhibited fEPSPs per se, and disturbed insulin's effect on fEPSP. Insulin also caused depotentiation during LTP expression and triggered depression during LTD recovery. Given the essential roles of dynamic synaptic transmission and plasticity in learning and memory, our data provide more evidence that insulin application may actively modulate hippocampal-dependent cognitive events.

Burst Detection Methods

'Bursting', defined as periods of high-frequency firing of a neuron separated by periods of quiescence, has been observed in various neuronal systems, both in vitro and in vivo. It has been associated with a range of neuronal processes, including efficient information transfer and the formation of functional networks during development, and has been shown to be sensitive to genetic and pharmacological manipulations. Accurate detection of periods of bursting activity is thus an important aspect of characterising both spontaneous and evoked neuronal network activity. A wide variety of computational methods have been developed to detect periods of bursting in spike trains recorded from neuronal networks. In this chapter, we review several of the most popular and successful of these methods.

Adaptive Optimization of Visual Sensitivity

Sensory systems adapt to environmental change. It has been argued that adaptation should have the effect of optimizing sensitivity to the new environment. Here we consider a framework in which this premise is made concrete using an economic normative theory of visual motion perception. In this framework, visual systems adapt to the environment by reallocating their limited neural resources. The allocation is optimal when uncertainties about different aspects of stimulation are balanced. This theory makes predictions about visual sensitivity as a function of environmental statistics. Adaptive optimization of the visual system should be manifested as a change in sensitivity for an observer and for the underlying motion-sensitive neurons. We review evidence supporting these predictions and examine effects of adaptation on the neuronal representation of visual motion.

Cortical travelling waves: mechanisms and computational principles

Multichannel recording technologies have revealed travelling waves of neural activity in multiple sensory, motor and cognitive systems. These waves can be spontaneously generated by recurrent circuits or evoked by external stimuli. They travel along brain networks at multiple scales, transiently modulating spiking and excitability as they pass. Here, we review recent experimental findings that have found evidence for travelling waves at single-area (mesoscopic) and whole-brain (macroscopic) scales. We place these findings in the context of the current theoretical understanding of wave generation and propagation in recurrent networks. During the large low-frequency rhythms of sleep or the relatively desynchronized state of the awake cortex, travelling waves may serve a variety of functions, from long-term memory consolidation to processing of dynamic visual stimuli. We explore new avenues for experimental and computational understanding of the role of spatiotemporal activity patterns in the cortex.

Hippocampal ripples down-regulate synapses

The specific effects of sleep on synaptic plasticity remain unclear. We report that mouse hippocampal sharp-wave ripple oscillations serve as intrinsic events that trigger long-lasting synaptic depression. Silencing of sharp-wave ripples during slow-wave states prevented the spontaneous down-regulation of net synaptic weights and impaired the learning of new memories. The synaptic down-regulation was dependent on the N-methyl-d-aspartate receptor and selective for a specific input pathway. Thus, our findings are consistent with the role of slow-wave states in refining memory engrams by reducing recent memory-irrelevant neuronal activity and suggest a previously unrecognized function for sharp-wave ripples.

The role of T-type calcium channels in the subiculum: to burst or not to burst?

KEY POINTS

Pharmacological, molecular and genetic data indicate a prominent role of low-voltage-activated T-type calcium channels (T-channels) in the firing activity of both pyramidal and inhibitory interneurons in the subiculum. Pharmacological inhibition of T-channels switched burst firing with lower depolarizing stimuli to regular spiking, and fully abolished hyperpolarization-induced burst firing. Our molecular studies showed that Ca_V 3.1 is the most abundantly expressed isoform of T-channels in the rat subiculum. Consistent with this finding, both regular-spiking and burst firing patterns were profoundly depressed in the mouse with global deletion of Ca_V 3.1 isoform of T-channels. Selective inhibition of T-channels and global deletion of Ca_V 3.1 channels completely suppressed development of long-term potentiation (LTP) in the CA1-subiculum, but not in the CA3-CA1 pathway.

ABSTRACT

Several studies suggest that voltage-gated calcium currents are involved in generating high frequency burst firing in the subiculum, but the exact nature of these currents remains unknown. Here, we used selective pharmacology, molecular and genetic approaches to implicate Cav3.1-containing T-channels in subicular burst firing, in contrast to several previous reports discounting T-channels as major contributors to subicular neuron physiology. Furthermore, pharmacological antagonism of T-channels, as well as global deletion of CaV3.1 isoform, completely suppressed development of long-term potentiation (LTP) in the CA1-subiculum, but not in the CA3-CA1 pathway. Our results indicate that excitability and synaptic plasticity of subicular neurons relies heavily on T-channels. Hence, T-channels may be a promising new drug target for different cognitive deficits.

Functional perturbation of forebrain principal neurons reveals differential effects in novel and well-learned tasks

Neural circuits in mammalian brains consist of large numbers of different cell types having different functional properties. To better understand the separate roles of individual neuron types in specific aspects of spatial learning and memory, we perturbed the function of principal neurons in vivo during maze performance or in hippocampal slices during recording of evoked excitatory synaptic potentials. Transgenic mice expressing the Drosophila allatostatin receptor (AlstR) in cortical and hippocampal pyramidal cells were tested on an elevated plus maze, in a Y-maze, and in the Morris water maze. Relative to a control cohort, AlstR-positive mice treated with allatostatin exhibited no difference in open arm dwell time on the elevated plus maze or total number of arm entries in a Y-maze, but displayed reduced spontaneous alternation. When animals received massed or spaced training trials in the Morris water maze, and the peptide was delivered prior to an immediate probe, no effects on performance were observed. When the peptide was delivered during a probe trial performed 24h after seven days of spaced training, allatostatin delivery to AlstR positive mice enhanced direct navigation to the escape platform. Combined, these results suggest that cortical and hippocampal pyramidal neurons are required during spatial decision-making in a novel environment and compete with other neural systems after extended training in a long-term reference memory task. In hippocampal slices collected from AlstR positive animals, allatostatin delivery produced frequency dependent alterations in the Schaffer collateral fiber volley (attenuated accommodation at 100Hz) and excitatory postsynaptic potential (attenuated facilitation at 5Hz). Combined, the neural and behavioral discoveries support the involvement of short-term plasticity of Schaffer collateral axons and synapses during exploration of a novel environment and during initial orientation to a goal in a well-learned setting.

Singing modulates parvalbumin interneurons throughout songbird forebrain vocal control circuitry

Across species, the performance of vocal signals can be modulated by the social environment. Zebra finches, for example, adjust their song performance when singing to females ('female-directed' or FD song) compared to when singing in isolation ('undirected' or UD song). These changes are salient, as females prefer the FD song over the UD song. Despite the importance of these performance changes, the neural mechanisms underlying this social modulation remain poorly understood. Previous work in finches has established that expression of the immediate early gene EGR1 is increased during singing and modulated by social context within the vocal control circuitry. Here, we examined whether particular neural subpopulations within those vocal control regions exhibit similar modulations of EGR1 expression. We compared EGR1 expression in neurons expressing parvalbumin (PV), a calcium buffer that modulates network plasticity and homeostasis, among males that performed FD song, males that produced UD song, or males that did not sing. We found that, overall, singing but not social context significantly affected EGR1 expression in PV neurons throughout the vocal control nuclei. We observed differences in EGR1 expression between two classes of PV interneurons in the basal ganglia nucleus Area X. Additionally, we found that singing altered the amount of PV expression in neurons in HVC and Area X and that distinct PV interneuron types in Area X exhibited different patterns of modulation by singing. These data indicate that throughout the vocal control circuitry the singing-related regulation of EGR1 expression in PV neurons may be less influenced by social context than in other neuron types and raise the possibility of cell-type specific differences in plasticity and calcium buffering.

Microglia Function in the Central Nervous System During Health and Neurodegeneration

Microglia are resident cells of the brain that regulate brain development, maintenance of neuronal networks, and injury repair. Microglia serve as brain macrophages but are distinct from other tissue macrophages owing to their unique homeostatic phenotype and tight regulation by the central nervous system (CNS) microenvironment. They are responsible for the elimination of microbes, dead cells, redundant synapses, protein aggregates, and other particulate and soluble antigens that may endanger the CNS. Furthermore, as the primary source of proinflammatory cytokines, microglia are pivotal mediators of neuroinflammation and can induce or modulate a broad spectrum of cellular responses. Alterations in microglia functionality are implicated in brain development and aging, as well as in neurodegeneration. Recent observations about microglia ontogeny combined with extensive gene expression profiling and novel tools to study microglia biology have allowed us to characterize the spectrum of microglial phenotypes during development, homeostasis, and disease. In this article, we review recent advances in our understanding of the biology of microglia, their contribution to homeostasis, and their involvement in neurodegeneration. Moreover, we highlight the complexity of targeting microglia for therapeutic intervention in neurodegenerative diseases.

Neural plasticity during motor learning with motor imagery practice: Review and perspectives

In the last decade, many studies confirmed the benefits of mental practice with motor imagery. In this review we first aimed to compile data issued from fundamental and clinical investigations and to provide the key-components for the optimization of motor imagery strategy. We focused on transcranial magnetic stimulation studies, supported by brain imaging research, that sustain the current hypothesis of a functional link between cortical reorganization and behavioral improvement. As perspectives, we suggest a model of neural adaptation following mental practice, in which synapse conductivity and inhibitory mechanisms at the spinal level may also play an important role.

Early Impairment of Synaptic and Intrinsic Excitability in Mice Expressing ALS/Dementia-Linked Mutant UBQLN2

Frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) are believed to represent the different outcomes of a common pathogenic mechanism. However, while researchers have intensely studied the involvement of motor neurons in the ALS/FTD syndrome, very little is known about the function of hippocampal neurons, although this area is critical for memory and other cognitive functions. We investigated the electrophysiological properties of CA1 pyramidal cells in slices from 1 month-old UBQLN2^P497H mice, a recently generated model of ALS/FTD that shows heavy depositions of ubiquilin2-positive aggregates in this brain region. We found that, compared to wild-type mice, cells from UBQLN2^P497H mice were hypo-excitable. The amplitude of the glutamatergic currents elicited by afferent fiber stimulation was reduced by ~50%, but no change was detected in paired-pulse plasticity. The maximum firing frequency in response to depolarizing current injection was reduced by ~30%; the fast afterhyperpolarization in response to a range of depolarizations was reduced by almost 10 mV; the maximum slow afterhyperpolarization (sAHP) was also significantly decreased, likely in consequence of the decreased number of spikes. Finally, the action potential (AP) upstroke was blunted and the threshold depolarized compared to controls. Thus, synaptic and intrinsic excitability are both impaired in CA1 pyramidal cells of UBQLN2^P497H mice, likely constituting a cellular mechanism for the cognitive impairments. Because these alterations are detectable before the establishment of overt pathology, we hypothesize that they may affect the further course of the disease.

Structural Plasticity, Effectual Connectivity, and Memory in Cortex

Learning and memory is commonly attributed to the modification of synaptic strengths in neuronal networks. More recent experiments have also revealed a major role of structural plasticity including elimination and regeneration of synapses, growth and retraction of dendritic spines, and remodeling of axons and dendrites. Here we work out the idea that one likely function of structural plasticity is to increase "effectual connectivity" in order to improve the capacity of sparsely connected networks to store Hebbian cell assemblies that are supposed to represent memories. For this we define effectual connectivity as the fraction of synaptically linked neuron pairs within a cell assembly representing a memory. We show by theory and numerical simulation the close links between effectual connectivity and both information storage capacity of neural networks and effective connectivity as commonly employed in functional brain imaging and connectome analysis. Then, by applying our model to a recently proposed memory model, we can give improved estimates on the number of cell assemblies that can be stored in a cortical macrocolumn assuming realistic connectivity. Finally, we derive a simplified model of structural plasticity to enable large scale simulation of memory phenomena, and apply our model to link ongoing adult structural plasticity to recent behavioral data on the spacing effect of learning.

Memory in Neuroscience: Rhetoric Versus Reality

The central point of this article is that the concept of memory as information storage in the brain is inadequate for and irrelevant to understanding the nervous system. Beginning from the sensorimotor hypothesis that underlies neuroscience—that the entire function of the nervous system is to connect experience to appropriate behavior—the paper defines memories as sequences of events that connect remote experience to present behavior. Their essential components are (a) persistent events that bridge the time from remote experience to present behavior and (b) junctional events in which connections from remote experience and recent experience merge to produce behavior. The sequences comprising even the simplest memories are complex. This is both necessary—to preserve previously learned behaviors—and inevitable—due to secondary activity-driven plasticity. This complexity further highlights the inadequacy of the information storage concept and the importance of extreme simplicity in models used to study memory.

More Gamma More Predictions: Gamma-Synchronization as a Key Mechanism for Efficient Integration of Classical Receptive Field Inputs with Surround Predictions

During visual stimulation, neurons in visual cortex often exhibit rhythmic and synchronous firing in the gamma-frequency (30–90 Hz) band. Whether this phenomenon plays a functional role during visual processing is not fully clear and remains heavily debated. In this article, we explore the function of gamma-synchronization in the context of predictive and efficient coding theories. These theories hold that sensory neurons utilize the statistical regularities in the natural world in order to improve the efficiency of the neural code, and to optimize the inference of the stimulus causes of the sensory data. In visual cortex, this relies on the integration of classical receptive field (CRF) data with predictions from the surround. Here we outline two main hypotheses about gamma-synchronization in visual cortex. First, we hypothesize that the precision of gamma-synchronization reflects the extent to which CRF data can be accurately predicted by the surround. Second, we hypothesize that different cortical columns synchronize to the extent that they accurately predict each other’s CRF visual input. We argue that these two hypotheses can account for a large number of empirical observations made on the stimulus dependencies of gamma-synchronization. Furthermore, we show that they are consistent with the known laminar dependencies of gamma-synchronization and the spatial profile of intercolumnar gamma-synchronization, as well as the dependence of gamma-synchronization on experience and development. Based on our two main hypotheses, we outline two additional hypotheses. First, we hypothesize that the precision of gamma-synchronization shows, in general, a negative dependence on RF size. In support, we review evidence showing that gamma-synchronization decreases in strength along the visual hierarchy, and tends to be more prominent in species with small V1 RFs. Second, we hypothesize that gamma-synchronized network dynamics facilitate the emergence of spiking output that is particularly information-rich and sparse.

Plasticity of intrinsic excitability in mature granule cells of the dentate gyrus

The dentate gyrus is the main entry gate for cortical input to the hippocampus and one of the few brain areas where adult neurogenesis occurs. Several studies have shown that it is relatively difficult to induce synaptic plasticity in mature but not in newborn dentate granule cells. In the present work we have systematically addressed how classical protocols to induce synaptic plasticity affect action potential firing and intrinsic excitability in mature granule cells. We found that stimulation paradigms considered to be relevant for learning processes consistently modified the probability to generate action potentials in response to a given synaptic input in mature cells, in some paradigms even without any modification of synaptic strength. Collectively the results suggest that plasticity of intrinsic dendritic excitability has a lower induction-threshold than synaptic plasticity in mature granule cells and that this form of plasticity might be an important mechanism by which mature granule cells contribute to hippocampal function.

Roles of Presynaptic NMDA Receptors in Neurotransmission and Plasticity

Presynaptic NMDA receptors (preNMDARs) play pivotal roles in excitatory neurotransmission and synaptic plasticity. They facilitate presynaptic neurotransmitter release and modulate mechanisms controlling synaptic maturation and plasticity during formative periods of brain development. There is an increasing understanding of the roles of preNMDARs in experience-dependent synaptic and circuit-specific computation. In this review we summarize the latest understanding of compartment-specific expression and function of preNMDARs, and how they contribute to synapse-specific and circuit-level information processing.

Concomitant histone deacetylase and phosphodiesterase 5 inhibition synergistically prevents the disruption in synaptic plasticity and it reverses cognitive impairment in a mouse model of Alzheimer's disease

BACKGROUND

Given the implication of histone acetylation in memory processes, histone deacetylase inhibitors (HDACIs) have been postulated as potential modulators of cognitive impairment in Alzheimer's disease (AD). However, dose-dependent side effects have been described in patients with the currently available broad-spectrum HDACIs, explaining why their therapeutic potential has not been realized for chronic diseases. Here, by simultaneously targeting two independent enzyme activities, histone deacetylase (HDAC) and phosphodiesterase-5 (PDE5), we propose a novel mode of inhibitory action that might increase the therapeutic specificity of HDACIs.

RESULTS

The combination of vorinostat, a pan-HDACI, and tadalafil, a PDE5 inhibitor, rescued the long-term potentiation impaired in slices from APP/PS1 mice. When administered in vivo, the combination of these drugs alleviated the cognitive deficits in AD mice, as well as the amyloid and tau pathology, and it reversed the reduced dendritic spine density on hippocampal neurons. Significantly, the combination of vorinostat and tadalafil was more effective than each drug alone, both against the symptoms and in terms of disease modification, and importantly, these effects persisted after a 4-week washout period.

CONCLUSIONS

The results highlight the pharmacological potential of a combination of molecules that inhibit HDAC and PDE5 as a therapeutic approach for AD treatment.

Memory engram storage and retrieval

A great deal of experimental investment is directed towards questions regarding the mechanisms of memory storage. Such studies have traditionally been restricted to investigation of the anatomical structures, physiological processes, and molecular pathways necessary for the capacity of memory storage, and have avoided the question of how individual memories are stored in the brain. Memory engram technology allows the labeling and subsequent manipulation of components of specific memory engrams in particular brain regions, and it has been established that cell ensembles labeled by this method are both sufficient and necessary for memory recall. Recent research has employed this technology to probe fundamental questions of memory consolidation, differentiating between mechanisms of memory retrieval from the true neurobiology of memory storage.

Thalamic theta phase alignment predicts human memory formation and anterior thalamic cross-frequency coupling

Previously we reported electrophysiological evidence for a role for the anterior thalamic nucleus (ATN) in human memory formation (Sweeney-Reed et al., 2014). Theta-gamma cross-frequency coupling (CFC) predicted successful memory formation, with the involvement of gamma oscillations suggesting memory-relevant local processing in the ATN. The importance of the theta frequency range in memory processing is well-established, and phase alignment of oscillations is considered to be necessary for synaptic plasticity. We hypothesized that theta phase alignment in the ATN would be necessary for memory encoding. Further analysis of the electrophysiological data reveal that phase alignment in the theta rhythm was greater during successful compared with unsuccessful encoding, and that this alignment was correlated with the CFC. These findings support an active processing role for the ATN during memory formation.

DOI:http://dx.doi.org/10.7554/eLife.07578.001

In vitro studies of neuronal networks and synaptic plasticity in invertebrates and in mammals using multielectrode arrays

Brain functions are strictly dependent on neural connections formed during development and modified during life. The cellular and molecular mechanisms underlying synaptogenesis and plastic changes involved in learning and memory have been analyzed in detail in simple animals such as invertebrates and in circuits of mammalian brains mainly by intracellular recordings of neuronal activity. In the last decades, the evolution of techniques such as microelectrode arrays (MEAs) that allow simultaneous, long-lasting, noninvasive, extracellular recordings from a large number of neurons has proven very useful to study long-term processes in neuronal networks in vivo and in vitro. In this work, we start off by briefly reviewing the microelectrode array technology and the optimization of the coupling between neurons and microtransducers to detect subthreshold synaptic signals. Then, we report MEA studies of circuit formation and activity in invertebrate models such as Lymnaea, Aplysia, and Helix. In the following sections, we analyze plasticity and connectivity in cultures of mammalian dissociated neurons, focusing on spontaneous activity and electrical stimulation. We conclude by discussing plasticity in closed-loop experiments.

The Theory of Neural Cognition Applied to Robotics

The Theory of neural Cognition (TnC) states that the brain does not process information, it only represents information (i.e., it is ‘only’ a memory). The TnC explains how a memory can become an actor pursuing various goals, and proposes explanations concerning the implementation of a large variety of cognitive abilities, such as attention, memory, language, planning, intelligence, emotions, motivation, pleasure, consciousness and personality. The explanatory power of this new framework extends further though, to tackle special psychological states such as hypnosis, the placebo effect and sleep, and brain diseases such as autism, Alzheimer's disease and schizophrenia. The most interesting findings concern robotics: because the TnC considers the cortical column to be the key cognitive unit (instead of the neuron), it reduces the requirements for a brain implementation to only 160,000 units (instead of 86 billion). A robot exhibiting human-like cognitive abilities is therefore within our reach.