Mechanisms Of Synaptic Plasticity Research Articles

Changes in regulators of lipid metabolism in the brain: a study of animal models of depression and hypothyroidism

Metabolic disturbances in the brain are assumed to be early changes involved in the pathogenesis of depression, and these alterations may be intensified by a deficiency of thyroid hormones. In contrast to glucose metabolism, the link between altered brain lipids and the pathogenesis of depression is poorly understood, therefore in the present study, we determine transcription factors and enzymes regulating cholesterol and fatty acid biosynthesis in the brain structures in an animal model of depression, hypothyroidism and the coexistence of these diseases.In used model of depression, a decrease in the active form of the transcription factor SREBP-2 in the hippocampus was demonstrated, thus suggesting a reduction in cholesterol biosynthesis. In turn, in the hypothyroidism model, the reduction of cholesterol biosynthesis in the frontal cortex was demonstrated by both the reduction of mature SREBP-2 and the concentration of enzymes involved in cholesterol biosynthesis. The lower expression of LDL receptors in the frontal cortex indicates the restriction of cholesterol uptake into the cells in the model of coexistence of depression and hypothyroidism. Moreover, the identified changes in the levels of SNAP-25, GLP-1R and GLP-2R pointed to disturbances in synaptic plasticity and neuroprotection mechanisms in the examined brain structures.In conclusion, a reduction in cholesterol synthesis in the hippocampus in the model of depression may be the reason for the reduction of synaptic plasticity, whereas a lower level of LDL-R occurring in the frontal cortex in rats from the model of depression and hypothyroidism coexistence could be the reason of anxiogenic and depression-like behaviors.

Purkinje Cell Activity Resonation Generates Rhythmic Behaviors at the Preferred Frequency of 8 Hz.

Neural activity exhibits oscillations, bursts, and resonance, enhancing responsiveness at preferential frequencies. For example, theta-frequency bursting and resonance in granule cells facilitate synaptic transmission and plasticity mechanisms at the input stage of the cerebellar cortex. However, whether theta-frequency bursting of Purkinje cells is involved in generating rhythmic behavior has remained neglected. We recorded and optogenetically modulated the simple and complex spike activity of Purkinje cells while monitoring whisker movements with a high-speed camera of awake, head-fixed mice. During spontaneous whisking, both simple spike activity and whisker movement exhibit peaks within the theta band. Eliciting either simple or complex spikes at frequencies ranging from 0.5 to 28 Hz, we found that 8 Hz is the preferred frequency around which the largest movement is induced. Interestingly, oscillatory whisker movements at 8 Hz were also generated when simple spike bursting was induced at 2 and 4 Hz, but never via climbing fiber stimulation. These results indicate that 8 Hz is the resonant frequency at which the cerebellar-whisker circuitry produces rhythmic whisking.

High-resolution imaging and manipulation of endogenous AMPA receptor surface mobility during synaptic plasticity and learning.

Regulation of synaptic neurotransmitter receptor content is a fundamental mechanism for tuning synaptic efficacy during experience-dependent plasticity and behavioral adaptation. However, experimental approaches to track and modify receptor movements in integrated experimental systems are limited. Exploiting AMPA-type glutamate receptors (AMPARs) as a model, we generated a knock-in mouse expressing the biotin acceptor peptide (AP) tag on the GluA2 extracellular N-terminal. Cell-specific introduction of biotin ligase allows the use of monovalent or tetravalent avidin variants to respectively monitor or manipulate the surface mobility of endogenous AMPAR containing biotinylated AP–GluA2 in neuronal subsets. AMPAR immobilization precluded the expression of long-term potentiation and formation of contextual fear memory, allowing target-specific control of the expression of synaptic plasticity and animal behavior. The AP tag knock-in model offers unprecedented access to resolve and control the spatiotemporal dynamics of endogenous receptors, and opens new avenues to study the molecular mechanisms of synaptic plasticity and learning.

Brain structure and synaptic protein expression alterations after antidepressant treatment in a Wistar–Kyoto rat model of depression

BackgroundStructural MRI has demonstrated brain alterations in depression pathology and antidepressants treatment. While synaptic plasticity has been previously proposed as the potential underlying mechanism of MRI findings at a cellular and molecular scale, there is still insufficient evidence to link the MRI findings and synaptic plasticity mechanisms in depression pathology. MethodsIn this study, a Wistar-Kyoto (WKY) depression rat model was treated with antidepressants (citalopram or Jie-Yu Pills) and tested in a series of behavioral tests and a 7.0 MRI scanner. We then measured dendritic spine density within altered brain regions. We also examined expression of synaptic marker proteins (PSD-95 and SYP). ResultsWKY rats exhibited depression-like behaviors in the sucrose preference test (SPT) and forced swim test (FST), and anxiety-like behaviors in the open field test (OFT). Both antidepressants reversed behavioral changes in SPT and OFT but not in FST. We found a correlation between SPT performance and brain volumes as detected by MRI. All structural changes were consistent with alterations of the corpus callosum (white matter), dendritic spine density, as well as PSD95 and SYP expression at different levels. Two antidepressants similarly reversed these macro- and micro-changes. LimitationsThe single dose of antidepressants was the major limitation of this study. Further studies should focus on the white matter microstructure changes and myelin-related protein alterations, in addition to comparing the effects of ketamine. ConclusionTranslational evidence links structural MRI changes and synaptic plasticity alterations, which promote our understanding of SPT mechanisms and antidepressant response in WKY rats.

Arc weakens synapses by dispersing AMPA receptors from postsynaptic density via modulating PSD phase separation.

In response to stimuli, the immediate early gene product Arc can acutely down-regulate synaptic strength by removing AMPA receptors (AMPARs) from synapses and thus regulate synaptic plasticity. How Arc, a scaffold protein, can specifically facilitate synaptic removal of AMPARs is unknown. We found that Arc directly antagonizes with PSD-95 in binding to TARPs, which are the auxiliary subunits of AMPARs. Arc, in a highly concentration-sensitive manner, acutely disperses TARPs from the postsynaptic density (PSD) condensate formed via phase separation. TARPs with the Ser residue in the "P-S-Y"-motif of its tail phosphorylated are completely refractory from being dispersed by Arc, suggesting that Arc cannot displace AMPARs from PSDs in active synapses. Conversely, strengthening the interaction between Arc and TARPs enhances Arc's capacity in weakening synapses. Thus, Arc can specifically and effectively modulate synaptic AMPAR clustering via modulating PSD phase separation. Our study further suggests that activity-dependent, bi-directional modulation of PSD condensate formation/dispersion represents a general regulatory mechanism for synaptic plasticity.

Editorial: Cellular and molecular mechanisms of synaptic plasticity at hippocampal and cortical synapses

Editorial: Cellular and molecular mechanisms of synaptic plasticity at hippocampal and cortical synapses

Aβ/Amyloid Precursor Protein-Induced Hyperexcitability and Dysregulation of Homeostatic Synaptic Plasticity in Neuron Models of Alzheimer's Disease.

Alzheimer’s disease (AD) is increasingly seen as a disease of synapses and diverse evidence has implicated the amyloid-β peptide (Aβ) in synapse damage. The molecular and cellular mechanism(s) by which Aβ and/or its precursor protein, the amyloid precursor protein (APP) can affect synapses remains unclear. Interestingly, early hyperexcitability has been described in human AD and mouse models of AD, which precedes later hypoactivity. Here we show that neurons in culture with either elevated levels of Aβ or with human APP mutated to prevent Aβ generation can both induce hyperactivity as detected by elevated calcium transient frequency and amplitude. Since homeostatic synaptic plasticity (HSP) mechanisms normally maintain a setpoint of activity, we examined whether HSP was altered in AD transgenic neurons. Using methods known to induce HSP, we demonstrate that APP protein levels are regulated by chronic modulation of activity and that AD transgenic neurons have an impaired adaptation of calcium transients to global changes in activity. Further, AD transgenic compared to WT neurons failed to adjust the length of their axon initial segments (AIS), an adaptation known to alter excitability. Thus, we show that both APP and Aβ influence neuronal activity and that mechanisms of HSP are disrupted in primary neuron models of AD.

Traces of semantization - from episodic to semantic memory in a spiking cortical network model.

Episodic memory is a recollection of past personal experiences associated with particular times and places. This kind of memory is commonly subject to loss of contextual information or “semantization,” which gradually decouples the encoded memory items from their associated contexts while transforming them into semantic or gist-like representations. Novel extensions to the classical Remember/Know (R/K) behavioral paradigm attribute the loss of episodicity to multiple exposures of an item in different contexts. Despite recent advancements explaining semantization at a behavioral level, the underlying neural mechanisms remain poorly understood. In this study, we suggest and evaluate a novel hypothesis proposing that Bayesian–Hebbian synaptic plasticity mechanisms might cause semantization of episodic memory. We implement a cortical spiking neural network model with a Bayesian–Hebbian learning rule called Bayesian Confidence Propagation Neural Network (BCPNN), which captures the semantization phenomenon and offers a mechanistic explanation for it. Encoding items across multiple contexts leads to item-context decoupling akin to semantization. We compare BCPNN plasticity with the more commonly used spike-timing-dependent plasticity (STDP) learning rule in the same episodic memory task. Unlike BCPNN, STDP does not explain the decontextualization process. We further examine how selective plasticity modulation of isolated salient events may enhance preferential retention and resistance to semantization. Our model reproduces important features of episodicity on behavioral timescales under various biological constraints while also offering a novel neural and synaptic explanation for semantization, thereby casting new light on the interplay between episodic and semantic memory processes.

Sequence learning, prediction, and replay in networks of spiking neurons

Sequence learning, prediction and replay have been proposed to constitute the universal computations performed by the neocortex. The Hierarchical Temporal Memory (HTM) algorithm realizes these forms of computation. It learns sequences in an unsupervised and continuous manner using local learning rules, permits a context specific prediction of future sequence elements, and generates mismatch signals in case the predictions are not met. While the HTM algorithm accounts for a number of biological features such as topographic receptive fields, nonlinear dendritic processing, and sparse connectivity, it is based on abstract discrete-time neuron and synapse dynamics, as well as on plasticity mechanisms that can only partly be related to known biological mechanisms. Here, we devise a continuous-time implementation of the temporal-memory (TM) component of the HTM algorithm, which is based on a recurrent network of spiking neurons with biophysically interpretable variables and parameters. The model learns high-order sequences by means of a structural Hebbian synaptic plasticity mechanism supplemented with a rate-based homeostatic control. In combination with nonlinear dendritic input integration and local inhibitory feedback, this type of plasticity leads to the dynamic self-organization of narrow sequence-specific subnetworks. These subnetworks provide the substrate for a faithful propagation of sparse, synchronous activity, and, thereby, for a robust, context specific prediction of future sequence elements as well as for the autonomous replay of previously learned sequences. By strengthening the link to biology, our implementation facilitates the evaluation of the TM hypothesis based on experimentally accessible quantities. The continuous-time implementation of the TM algorithm permits, in particular, an investigation of the role of sequence timing for sequence learning, prediction and replay. We demonstrate this aspect by studying the effect of the sequence speed on the sequence learning performance and on the speed of autonomous sequence replay.

Coordination chemogenetics for activation of GPCR-type glutamate receptors in brain tissue

Direct activation of cell-surface receptors is highly desirable for elucidating their physiological roles. A potential approach for cell-type-specific activation of a receptor subtype is chemogenetics, in which both point mutagenesis of the receptors and designed ligands are used. However, ligand-binding properties are affected in most cases. Here, we developed a chemogenetic method for direct activation of metabotropic glutamate receptor 1 (mGlu1), which plays essential roles in cerebellar functions in the brain. Our screening identified a mGlu1 mutant, mGlu1(N264H), that was activated directly by palladium complexes. A palladium complex showing low cytotoxicity successfully activated mGlu1 in mGlu1(N264H) knock-in mice, revealing that activation of endogenous mGlu1 is sufficient to evoke the critical cellular mechanism of synaptic plasticity, a basis of motor learning in the cerebellum. Moreover, cell-type-specific activation of mGlu1 was demonstrated successfully using adeno-associated viruses in mice, which shows the potential utility of this chemogenetics for clarifying the physiological roles of mGlu1 in a cell-type-specific manner.

Norepinephrine potentiates and serotonin depresses visual cortical responses by transforming eligibility traces

Reinforcement allows organisms to learn which stimuli predict subsequent biological relevance. Hebbian mechanisms of synaptic plasticity are insufficient to account for reinforced learning because neuromodulators signaling biological relevance are delayed with respect to the neural activity associated with the stimulus. A theoretical solution is the concept of eligibility traces (eTraces), silent synaptic processes elicited by activity which upon arrival of a neuromodulator are converted into a lasting change in synaptic strength. Previously we demonstrated in visual cortical slices the Hebbian induction of eTraces and their conversion into LTP and LTD by the retroactive action of norepinephrine and serotonin Here we show in vivo in mouse V1 that the induction of eTraces and their conversion to LTP/D by norepinephrine and serotonin respectively potentiates and depresses visual responses. We also show that the integrity of this process is crucial for ocular dominance plasticity, a canonical model of experience-dependent plasticity.

Enhanced Non-Associative Long-Term Potentiation in Immature Granule Cells in the Dentate Gyrus of Adult Rats.

The dentate gyrus is one of the few sites of neurogenesis in the adult brain. Integration of new-generated granule cells into the hippocampal circuitry provides a substrate for structural plasticity, fundamental for normal function of adult hippocampus. However, mechanisms of synaptic plasticity that mediate integration of new-generated granule cells into the existing circuitry remain poorly understood. Especially mechanisms of plasticity at GABA-ergic synapses remain elusive. Here, we show that postsynaptic spiking without presynaptic activation can induce heterosynaptic, non-associative plasticity at GABA-ergic inputs to both immature and mature granule cells. In both immature and mature neurons, plastic changes were bidirectional and individual inputs could express long-term potentiation (LTP) or long-term depression (LTD), or do not change. However, properties of non-associative plasticity dramatically change with maturation of newly generated granule cells: while in immature cells there was a clear predominance of non-associative LTP and net potentiation across the inputs, in mature neurons, potentiation and depression were balanced with no net change on average. We conclude that GABA-ergic inputs to granule cells are plastic, and that the rules for induction of non-associative plasticity change with maturation. We propose that potentiation-biased non-associative plasticity of GABA-ergic transmission might help to counter-balance an increase of excitatory drive that is facilitated by enhanced LTP at glutamatergic synapses in maturating granule cells. Such mechanism might help to build a strong GABA-ergic input to surviving active new cells, necessary for normal function of mature granule cells, which operate under a tight inhibitory control and generate sparse spiking activity.

Bioinformatic Analysis of Epigenomic Studies for Major Depressive Disorder

Background: Major depressive disorder (MDD) is a common psychiatric entity, being characterized by alterations in mood and in other clinical dimensions. Several epigenome-wide association studies (EWAS) for MDD have been published. Here, we aimed to identify common genes in EWAS and their convergence with multiple lines of genomic evidence. Methods: We carried out a computational analysis using data of EWAS, which included a meta-analysis for brain samples of MDD, a convergence analysis for brain and blood samples, and top results from available genome-wide expression and association data. Functional enrichment and protein-protein interaction network analyses were also done. Results: The meta-analysis for brain samples detected a significant gene, FAM53B. A list of forty-four top differentially methylated (DM) candidate genes was found, including GRM8, NOTCH4 and SEMA6A, in addition to known druggable genes. The binding-sites for brain-expressed transcription factors, CREB and FOXO1, were enriched in the top DM genes. The protein-protein interaction networks showed that DM genes for MDD, such as RPRM and TMEM14B, play a central role. Conclusion: In this study, we found integrative evidence for the possible role of novel candidate genes and pathways. These genes are involved in mechanisms of synaptic plasticity, which have been associated with several psychiatric disorders. Analysis of epigenetic factors have a great potential for the identification of the mechanisms involved in the pathogenesis of MDD, taking into account their possible role in the interaction between genetic factors and the environment.

Paradoxical somatodendritic decoupling supports cortical plasticity during REM sleep.

Rapid eye movement (REM) sleep is associated with the consolidation of emotional memories. Yet, the underlying neocortical circuits and synaptic mechanisms remain unclear. We found that REM sleep is associated with a somatodendritic decoupling in pyramidal neurons of the prefrontal cortex. This decoupling reflects a shift of inhibitory balance between parvalbumin neuron-mediated somatic inhibition and vasoactive intestinal peptide-mediated dendritic disinhibition, mostly driven by neurons from the central medial thalamus. REM-specific optogenetic suppression of dendritic activity led to a loss of danger-versus-safety discrimination during associative learning and a lack of synaptic plasticity, whereas optogenetic release of somatic inhibition resulted in enhanced discrimination and synaptic potentiation. Somatodendritic decoupling during REM sleep promotes opposite synaptic plasticity mechanisms that optimize emotional responses to future behavioral stressors.

Altered closed state inactivation gating in Kv4.2 channels results in developmental and epileptic encephalopathies in human patients.

Kv4.2 subunits, encoded by KCND2, serve as the pore-forming components of voltage-gated, inactivating ISA K+ channels expressed in the brain. ISA channels inactivate without opening in response to subthreshold excitatory input, temporarily increasing neuronal excitability, the back propagation of action potentials, and Ca2+ influx into dendrites, thereby regulating mechanisms of spike timing-dependent synaptic plasticity. As previously described, a de novo variant in Kv4.2, p.Val404Met, is associated with an infant-onset developmental and epileptic encephalopathyin monozygotic twin boys. The p.Val404Met variant enhances inactivation directly from closed states, but dramatically impairs inactivation after channel opening. We now report the identification of a closely related, novel, de novo variant in Kv4.2, p.Val402Leu, in a boy with an early-onset pharmacoresistant epilepsy that evolved to an epileptic aphasia syndrome (Continuous Spike Wave during Sleep Syndrome). Like p.Val404Met, the p.Val402Leu variant increases the rate of inactivation from closed states, but significantly slows inactivation after the pore opens. Although quantitatively the p.Val402Leu mutation alters channel kinetics less dramatically than p.Val404Met, our results strongly support the conclusion that p.Val402Leu and p.Val404Met cause the clinical features seen in the affected individuals and underscore the importance of closed state inactivation in ISA channels in normal brain development and function.

On The Biophysical Complexity of Brain Dynamics: An Outlook

The human brain is a complex network whose ensemble time evolution is directed by the cumulative interactions of its cellular components, such as neurons and glia cells. Coupled through chemical neurotransmission and receptor activation, these individuals interact with one another to varying degrees by triggering a variety of cellular activity from internal biological reconfigurations to external interactions with other network agents. Consequently, such local dynamic connections mediating the magnitude and direction of influence cells have on one another are highly nonlinear and facilitate, respectively, nonlinear and potentially chaotic multicellular higher-order collaborations. Thus, as a statistical physical system, the nonlinear culmination of local interactions produces complex global emergent network behaviors, enabling the highly dynamical, adaptive, and efficient response of a macroscopic brain network. Microstate reconfigurations are typically facilitated through synaptic and structural plasticity mechanisms that alter the degree of coupling (magnitude of influence) neurons have upon each other, dictating the type of coordinated macrostate emergence in populations of neural cells. These can emerge in the form of local regions of synchronized clusters about a center frequency composed of individual neural cell collaborations as a fundamental form of collective organization. A single mode of synchronization is insufficient for the computational needs of the brain. Thus, as neural components influence one another (cellular components, multiple clusters of synchronous populations, brain nuclei, and even brain regions), different patterns of neural behavior interact with one another to produce an emergent spatiotemporal spectral bandwidth of neural activity corresponding to the dynamical state of the brain network. Furthermore, hierarchical and self-similar structures support these network properties to operate effectively and efficiently. Neuroscience has come a long way since its inception; however, a comprehensive and intuitive understanding of how the brain works is still amiss. It is becoming evident that any singular perspective upon the grandiose biophysical complexity within the brain is inadequate. It is the purpose of this paper to provide an outlook through a multitude of perspectives, including the fundamental biological mechanisms and how these operate within the physical constraints of nature. Upon assessing the state of prior research efforts, in this paper, we identify the path future research effort should pursue to inspire progress in neuroscience.

Choice-selective sequences dominate in cortical relative to thalamic inputs to NAc to support reinforcement learning.

SUMMARYHow are actions linked with subsequent outcomes to guide choices? The nucleus accumbens, which is implicated in this process, receives glutamatergic inputs from the prelimbic cortex and midline regions of the thalamus. However, little is known about whether and how representations differ across these input pathways. By comparing these inputs during a reinforcement learning task in mice, we discovered that prelimbic cortical inputs preferentially represent actions and choices, whereas midline thalamic inputs preferentially represent cues. Choice-selective activity in the prelimbic cortical inputs is organized in sequences that persist beyond the outcome. Through computational modeling, we demonstrate that these sequences can support the neural implementation of reinforcement-learning algorithms, in both a circuit model based on synaptic plasticity and one based on neural dynamics. Finally, we test and confirm a prediction of our circuit models by direct manipulation of nucleus accumbens input neurons.

Spike-Timing-Dependent Plasticity Mediated by Dopamine and its Role in Parkinson's Disease Pathophysiology.

Parkinson's disease (PD) is a multi-systemic neurodegenerative brain disorder. Motor symptoms of PD are linked to the significant dopamine (DA) loss in substantia nigra pars compacta (SNc) followed by basal ganglia (BG) circuit dysfunction. Increasing experimental and computational evidence indicates that (synaptic) plasticity plays a key role in the emergence of PD-related pathological changes following DA loss. Spike-timing-dependent plasticity (STDP) mediated by DA provides a mechanistic model for synaptic plasticity to modify synaptic connections within the BG according to the neuronal activity. To shed light on how DA-mediated STDP can shape neuronal activity and synaptic connectivity in the PD condition, we reviewed experimental and computational findings addressing the modulatory effect of DA on STDP as well as other plasticity mechanisms and discussed their potential role in PD pathophysiology and related network dynamics and connectivity. In particular, reshaping of STDP profiles together with other plasticity-mediated processes following DA loss may abnormally modify synaptic connections in competing pathways of the BG. The cascade of plasticity-induced maladaptive or compensatory changes can impair the excitation-inhibition balance towards the BG output nuclei, leading to the emergence of pathological activity-connectivity patterns in PD. Pre-clinical, clinical as well as computational studies reviewed here provide an understanding of the impact of synaptic plasticity and other plasticity mechanisms on PD pathophysiology, especially PD-related network activity and connectivity, after DA loss. This review may provide further insights into the abnormal structure-function relationship within the BG contributing to the emergence of pathological states in PD. Specifically, this review is intended to provide detailed information for the development of computational network models for PD, serving as testbeds for the development and optimization of invasive and non-invasive brain stimulation techniques. Computationally derived hypotheses may accelerate the development of therapeutic stimulation techniques and potentially reduce the number of related animal experiments.

Strong Aversive Conditioning Triggers a Long-Lasting Generalized Aversion.

Generalization is an adaptive mnemonic process in which an animal can leverage past learning experiences to navigate future scenarios, but overgeneralization is a hallmark feature of anxiety disorders. Therefore, understanding the synaptic plasticity mechanisms that govern memory generalization and its persistence is an important goal. Here, we demonstrate that strong CTA conditioning results in a long-lasting generalized aversion that persists for at least 2 weeks. Using brain slice electrophysiology and activity-dependent labeling of the conditioning-active neuronal ensemble within the gustatory cortex, we find that strong CTA conditioning induces a long-lasting increase in synaptic strengths that occurs uniformly across superficial and deep layers of GC. Repeated exposure to salt, the generalized tastant, causes a rapid attenuation of the generalized aversion that correlates with a reversal of the CTA-induced increases in synaptic strength. Unlike the uniform strengthening that happens across layers, reversal of the generalized aversion results in a more pronounced depression of synaptic strengths in superficial layers. Finally, the generalized aversion and its reversal do not impact the acquisition and maintenance of the aversion to the conditioned tastant (saccharin). The strong correlation between the generalized aversion and synaptic strengthening, and the reversal of both in superficial layers by repeated salt exposure, strongly suggests that the synaptic changes in superficial layers contribute to the formation and reversal of the generalized aversion. In contrast, the persistence of synaptic strengthening in deep layers correlates with the persistence of CTA. Taken together, our data suggest that layer-specific synaptic plasticity mechanisms separately govern the persistence and generalization of CTA memory.

Butyric Acid Precursor Tributyrin Modulates Hippocampal Synaptic Plasticity and Prevents Spatial Memory Deficits: Role of PPARγ and AMPK.

BackgroundShort chain fatty acids (SCFA), such as butyric acid (BA), derived from the intestinal fermentation of dietary fiber and contained in dairy products, are gaining interest in relation to their possible beneficial effects on neuropsychological disordersMethodsC57BL/6J male mice were used to investigate the effect of tributyrin (TB), a prodrug of BA, on hippocampus (HIP)-dependent spatial memory, HIP synaptic transmission and plasticity mechanisms, and the expression of genes and proteins relevant to HIP glutamatergic transmission.ResultsEx vivo studies, carried out in HIP slices, revealed that TB can transform early-LTP into late-LTP (l-LTP) and to rescue LTP-inhibition induced by scopolamine. The facilitation of l-LTP induced by TB was blocked both by GW9662 (a PPARγ antagonist) and C-Compound (an AMPK inhibitor), suggesting the involvement of both PPARγ and AMPK on TB effects. Moreover, 48-hour intake of a diet containing 1% TB prevented, in adolescent but not in adult mice, scopolamine-induced impairment of HIP-dependent spatial memory. In the adolescent HIP, TB upregulated gene expression levels of Pparg, leptin, and adiponectin receptors, and that of the glutamate receptor subunits AMPA-2, NMDA-1, NMDA-2A, and NMDA-2B.ConclusionsOur study shows that TB has a positive influence on LTP and HIP-dependent spatial memory, which suggests that BA may have beneficial effects on memory.