Regional synapse gain and loss accompany memory formation in larval zebrafish

Defining the structural and functional changes in the nervous system underlying learning and memory represents a major challenge for modern neuroscience. Although changes in neuronal activity following memory formation have been studied [B. F. Grewe et al., Nature 543, 670–675 (2017); M. T. Rogan, U. V. Stäubli, J. E. LeDoux, Nature 390, 604–607 (1997)], the underlying structural changes at the synapse level remain poorly understood. Here, we capture synaptic changes in the midlarval zebrafish brain that occur during associative memory formation by imaging excitatory synapses labeled with recombinant probes using selective plane illumination microscopy. Imaging the same subjects before and after classical conditioning at single-synapse resolution provides an unbiased mapping of synaptic changes accompanying memory formation. In control animals and animals that failed to learn the task, there were no significant changes in the spatial patterns of synapses in the pallium, which contains the equivalent of the mammalian amygdala and is essential for associative learning in teleost fish [M. Portavella, J. P. Vargas, B. Torres, C. Salas, Brain Res. Bull. 57, 397–399 (2002)]. In zebrafish that formed memories, we saw a dramatic increase in the number of synapses in the ventrolateral pallium, which contains neurons active during memory formation and retrieval. Concurrently, synapse loss predominated in the dorsomedial pallium. Surprisingly, we did not observe significant changes in the intensity of synaptic labeling, a proxy for synaptic strength, with memory formation in any region of the pallium. Our results suggest that memory formation due to classical conditioning is associated with reciprocal changes in synapse numbers in the pallium.

Hebbian activity-dependent plasticity in white matter

Synaptic plasticity is required for learning and follows Hebb's Rule, the computational principle underpinning associative learning. In recent years, a complementary type of brain plasticity has been identified in myelinated axons, which make up the majority of brain's white matter. Like synaptic plasticity, myelin plasticity is required for learning, but it is unclear whether it is Hebbian or whether it follows different rules. Here, we provide evidence that white matter plasticity operates following Hebb's Rule in humans. Across two experiments, we find that co-stimulating cortical areas to induce Hebbian plasticity leads to relative increases in cortical excitability and associated increases in a myelin marker within the stimulated fiber bundle. We conclude that Hebbian plasticity extends beyond synaptic changes, and can be observed in human white matter fibers.

Localized Synaptic Potentiation is Necessary and Sufficient for Context Fear Memory

The nature and distribution of the synaptic changes that underlie memory are not well understood. We examined the synaptic plasticity behind context fear learning and found that conditioning produced potentiation of excitatory synapses specifically onto the basolateral amygdala neurons activated during learning. This synaptic potentiation lasted at least 7 days, and its disruption impaired memory recall. High frequency optogenetic stimulation of the CS and US-activated ensembles or biochemical induction of synaptic potentiation in US-responsive neurons alone was sufficient to produce a context fear association without prior associative training. These results suggest that plasticity of CS inputs onto US-responsive amygdala neurons is a necessary and sufficient step in forming context fear associations, and that context discrimination is determined by the CS-specific amygdala inputs activated during retrieval.

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 two 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.

General Anesthesia During Neurodevelopment Reduces Autistic Behavior in Adult BTBR Mice, a Murine Model of Autism

Preclinical studies suggest that repeated exposure to anesthetics during a critical period of neurodevelopment induces long-term changes in synaptic transmission, plasticity, and behavior. Such changes are of great concern, as similar changes have also been identified in animal models of neurodevelopmental disorders (NDDs) such as autism. Because of overlapping synaptic changes, it is also possible that anesthetic exposures have a more significant effect in individuals diagnosed with NDDs. Thus, we evaluated the effects of early, multiple anesthetic exposures in BTBR mice, an inbred strain that displays autistic behavior. We discovered that three cycles of sevoflurane anesthesia (2.5%, 1 h) with 2-h intervals between each exposure in late postnatal BTBR mice did not aggravate, but instead improved pathophysiological mechanisms involved with autistic behavior. Sevoflurane exposures restored E/I balance (by increasing inhibitory synaptic transmission), and increased mitochondrial respiration and BDNF signaling in BTBR mice. Most importantly, such changes were associated with reduced autistic behavior in BTBR mice, as sociability was increased in the three-chamber test and repetitive behavior was reduced in the self-grooming test. Our results suggest that anesthetic exposures during neurodevelopment may affect individuals diagnosed with NDDs differently.

Changes in TMS measures induced by repetitive TMS

Commonly used repetitive transcranial magnetic stimulation (rTMS) protocols, including regular rTMS, intermittent and continuous theta-burst stimulation (TBS) and quadripulse stimulation (QPS) are presented with respect to their induced neuromodulatory after-effects and the underlying cellular and synaptic neurophysiological mechanisms. The anatomical target is typically primary motor cortex since motor evoked potentials (MEPs) before and after the intervention can be used to assess effects of the respective rTMS protocol. High-frequency regular rTMS and intermittent TBS protocols tend to increase corticospinal excitability as indexed by MEP amplitude, whereas low-frequency regular rTMS and continuous TBS protocols tend to reduce corticospinal excitability. These effects are primarily due to LTP-like and LTD-like synaptic changes mediated by GABA and NMDA receptors. Changes in the balance between excitatory and inhibitory cortical microcircuits play a secondary role, with inconsistent effects as determined by paired-pulse TMS protocols. Finally, the challenge of large inter-subject response variability, and current directions of research to optimize rTMS effects through EEG-dependent personalized TMS are discussed.

Pinging the brain with visual impulses reveals electrically active, not activity-silent, working memories

Persistently active neurons during mnemonic periods have been regarded as the mechanism underlying working memory maintenance. Alternatively, neuronal networks could instead store memories in fast synaptic changes, thus avoiding the biological cost of maintaining an active code through persistent neuronal firing. Such “activity-silent” codes have been proposed for specific conditions in which memories are maintained in a nonprioritized state, as for unattended but still relevant short-term memories. A hallmark of this “activity-silent” code is that these memories can be reactivated from silent, synaptic traces. Evidence for “activity-silent” working memory storage has come from human electroencephalography (EEG), in particular from the emergence of decodability (EEG reactivations) induced by visual impulses (termed pinging) during otherwise “silent” periods. Here, we reanalyze EEG data from such pinging studies. We find that the originally reported absence of memory decoding reflects weak statistical power, as decoding is possible based on more powered analyses or reanalysis using alpha power instead of raw voltage. This reveals that visual pinging EEG “reactivations” occur in the presence of an electrically active, not silent, code for unattended memories in these data. This crucial change in the evidence provided by this dataset prompts a reinterpretation of the mechanisms of EEG reactivations. We provide 2 possible explanations backed by computational models, and we discuss the relationship with TMS-induced EEG reactivations.

Astrocytic microdomains from mouse cortex gain molecular control over long-term information storage and memory retention

Memory consolidation requires astrocytic microdomains for protein recycling; but whether this lays a mechanistic foundation for long-term information storage remains enigmatic. Here we demonstrate that persistent synaptic strengthening invited astrocytic microdomains to convert initially internalized (pro)-brain-derived neurotrophic factor (proBDNF) into active prodomain (BDNFpro) and mature BDNF (mBDNF) for synaptic re-use. While mBDNF activates TrkB, we uncovered a previously unsuspected function for the cleaved BDNFpro, which increases TrkB/SorCS2 receptor complex at post-synaptic sites. Astrocytic BDNFpro release reinforced TrkB phosphorylation to sustain long-term synaptic potentiation and to retain memory in the novel object recognition behavioral test. Thus, the switch from one inactive state to a multi-functional one of the proBDNF provides post-synaptic changes that survive the initial activation. This molecular asset confines local information storage in astrocytic microdomains to selectively support memory circuits.

Small, correlated changes in synaptic connectivity may facilitate rapid motor learning

Animals can rapidly adapt their movements to external perturbations. This adaptation is paralleled by changes in single neuron activity in the motor cortices. Behavioural and neural recording studies suggest that when animals learn to counteract a visuomotor perturbation, these changes originate from altered inputs to the motor cortices rather than from changes in local connectivity, as neural covariance is largely preserved during adaptation. Since measuring synaptic changes in vivo remains very challenging, we used a modular recurrent network model to compare the expected neural activity changes following learning through altered inputs (Hinput) and learning through local connectivity changes (Hlocal). Learning under Hinput produced small changes in neural activity and largely preserved the neural covariance, in good agreement with neural recordings in monkeys. Surprisingly given the presumed dependence of stable neural covariance on preserved circuit connectivity, Hlocal led to only slightly larger changes in neural activity and covariance compared to Hinput. This similarity is due to Hlocal only requiring small, correlated connectivity changes to counteract the perturbation, which provided the network with significant robustness against simulated synaptic noise. Simulations of tasks that impose increasingly larger behavioural changes revealed a growing difference between Hinput and Hlocal, which could be exploited when designing future experiments.