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Neurons can carry information with both the synchrony and rate of their spikes. However, it is unknown whether distinct subtypes of neurons are more sensitive to information carried by synchrony versus rate, or vice versa. Here, we address this question using patterned optical stimulation in slices of somatosensory cortex from mouse lines labelling fast-spiking (FS) and regular-spiking (RS) interneurons. We used optical stimulation in layer 2/3 to encode a 1-bit signal using either the synchrony or rate of activity. We then examined the mutual information between this signal and the interneuron responses. We found that for a synchrony encoding, FS interneurons carried more information in the first five milliseconds, while both interneuron subtypes carried more information than excitatory neurons in later responses. For a rate encoding, we found that RS interneurons carried more information after several milliseconds. These data demonstrate that distinct interneuron subtypes in the neocortex have distinct sensitivities to synchrony versus rate codes., In order to address whether distinct subtypes of neurons are more sensitive to information carried by synchrony versus rate, Prince et al. used optical stimulation in slices of somatosensory cortex from mouse lines labelling fast-spiking (FS) and regular-spiking (RS) interneurons. They demonstrated that FS and RS interneurons had differential sensitivity to changes in synchrony and rate, which advances our understanding of neural processing in the neocortex.

Behavioral flexibility is important in a changing environment. Previous research suggests that systems consolidation, a long-term poststorage process that alters memory traces, may reduce behavioral flexibility. However, exactly how systems consolidation affects flexibility is unknown. Here, we tested how systems consolidation affects: (1) flexibility in response to value changes and (2) flexibility in response to changes in the optimal sequence of actions. Mice were trained to obtain food rewards in a Y-maze by switching nose pokes between three arms. During initial training, all arms were rewarded and mice simply had to switch arms in order to maximize rewards. Then, after either a 1 or 28 d delay, we either devalued one arm, or we reinforced a specific sequence of pokes. We found that after a 1 d delay mice adapted relatively easily to the changes. In contrast, mice given a 28 d delay struggled to adapt, especially for changes to the optimal sequence of actions. Immediate early gene imaging suggested that the 28 d mice were less reliant on their hippocampus and more reliant on their medial prefrontal cortex. These data suggest that systems consolidation reduces behavioral flexibility, particularly for changes to the optimal sequence of actions.

Background Abnormal accumulation of amyloid β1–42 oligomers (AβO1–42), a hallmark of Alzheimer’s disease, impairs hippocampal theta-nested gamma oscillations and long-term potentiation (LTP) that are believed to underlie learning and memory. Parvalbumin-positive (PV) and somatostatin-positive (SST) interneurons are critically involved in theta-nested gamma oscillogenesis and LTP induction. However, how AβO1–42 affects PV and SST interneuron circuits is unclear. Through optogenetic manipulation of PV and SST interneurons and computational modeling of the hippocampal neural circuits, we dissected the contributions of PV and SST interneuron circuit dysfunctions on AβO1–42-induced impairments of hippocampal theta-nested gamma oscillations and oscillation-induced LTP. Results Targeted whole-cell patch-clamp recordings and optogenetic manipulations of PV and SST interneurons during in vivo-like, optogenetically induced theta-nested gamma oscillations in vitro revealed that AβO1–42 causes synapse-specific dysfunction in PV and SST interneurons. AβO1–42 selectively disrupted CA1 pyramidal cells (PC)-to-PV interneuron and PV-to-PC synapses to impair theta-nested gamma oscillogenesis. In contrast, while having no effect on PC-to-SST or SST-to-PC synapses, AβO1–42 selectively disrupted SST interneuron-mediated disinhibition to CA1 PC to impair theta-nested gamma oscillation-induced spike timing-dependent LTP (tLTP). Such AβO1–42-induced impairments of gamma oscillogenesis and oscillation-induced tLTP were fully restored by optogenetic activation of PV and SST interneurons, respectively, further supporting synapse-specific dysfunctions in PV and SST interneurons. Finally, computational modeling of hippocampal neural circuits including CA1 PC, PV, and SST interneurons confirmed the experimental observations and further revealed distinct functional roles of PV and SST interneurons in theta-nested gamma oscillations and tLTP induction. Conclusions Our results reveal that AβO1–42 causes synapse-specific dysfunctions in PV and SST interneurons and that optogenetic modulations of these interneurons present potential therapeutic targets for restoring hippocampal network oscillations and synaptic plasticity impairments in Alzheimer’s disease.

Systems neuroscience seeks explanations for how the brain implements a wide variety of perceptual, cognitive and motor tasks. Conversely, artificial intelligence attempts to design computational systems based on the tasks they will have to solve. In the case of artificial neural networks, the three components specified by design are the objective functions, the learning rules, and architectures. With the growing success of deep learning, which utilizes brain-inspired architectures, these three designed components have increasingly become central to how we model, engineer and optimize complex artificial learning systems. Here we argue that a greater focus on these components would also benefit systems neuroscience. We give examples of how this optimization-based framework can drive theoretical and experimental progress in neuroscience. We contend that this principled perspective on systems neuroscience will help to generate more rapid progress.

Anxiety is an adaptive response to potentially threatening situations. Exaggerated and uncontrolled anxiety responses become maladaptive and lead to anxiety disorders. Anxiety is shaped by a network of forebrain structures, including the hippocampus, septum, and prefrontal cortex. In particular, neural inputs arising from the ventral hippocampus (vHPC) to the lateral septum (LS) and medial prefrontal cortex (mPFC) are thought to serve as principal components of the anxiety circuit. However, the role of vHPC-to-LS and vHPC-to-mPFC signals in anxiety is unclear, as no study has directly compared their behavioral contribution at circuit level. We targeted LS-projecting vHPC cells and mPFC-projecting vHPC cells by injecting the retrogradely propagating canine adenovirus encoding Cre recombinase into the LS or mPFC, and injecting a Cre-responsive AAV (AAV8-hSyn-FLEX-hM3D or hM4D) into the vHPC. Consequences of manipulating these neurons were examined in well-established tests of anxiety. Chemogenetic manipulation of LS-projecting vHPC cells led to bidirectional changes in anxiety: activation of LS-projecting vHPC cells decreased anxiety whereas inhibition of these cells produced opposite anxiety-promoting effects. The observed anxiety-reducing function of LS-projecting cells was in contrast with the function of mPFC-projecting cells, which promoted anxiety. In addition, double retrograde tracing demonstrated that LS- and mPFC-projecting cells represent two largely anatomically distinct cell groups. Altogether, our findings suggest that the vHPC houses discrete populations of cells that either promote or suppress anxiety through differences in their projection targets. Disruption of the intricate balance in the activity of these two neuron populations may drive inappropriate behavioral responses seen in anxiety disorders.

Guaranteeing that synaptic plasticity leads to effective learning requires a means for assigning credit to each neuron for its contribution to behavior. The 'credit assignment problem' refers to the fact that credit assignment is non-trivial in hierarchical networks with multiple stages of processing. One difficulty is that if credit signals are integrated with other inputs, then it is hard for synaptic plasticity rules to distinguish credit-related activity from non-credit-related activity. A potential solution is to use the spatial layout and non-linear properties of dendrites to distinguish credit signals from other inputs. In cortical pyramidal neurons, evidence hints that top-down feedback signals are integrated in the distal apical dendrites and have a distinct impact on spike-firing and synaptic plasticity. This suggests that the distal apical dendrites of pyramidal neurons help the brain to solve the credit assignment problem.

SummaryThe ability to generate action potentials (spikes) in response to synaptic input determines whether a neuron participates in information processing. How a developing neuron becomes an active participant in a circuit or whether this process is activity dependent is not known, especially as spike-dependent plasticity mechanisms would not be available to non-spiking neurons. Here we use the optic tectum of awake Xenopus laevis tadpoles to determine how a neuron becomes able to generate sensory-driven spikes in vivo. At the onset of vision, many tectal neurons do not exhibit visual spiking behavior, despite being intrinsically excitable and receiving visuotopically organized synaptic inputs. However, a brief period of visual stimulation can drive these neurons to start generating stimulus-driven spikes. This conversion relies upon a selective increase in glutamatergic input and requires depolarizing GABAergic transmission and NMDA receptor activation. This permissive form of experience-dependent plasticity enables a neuron to start contributing to circuit function.

Following learning, increased coupling between spindle oscillations in the medial prefrontal cortex (mPFC) and ripple oscillations in the hippocampus is thought to underlie memory consolidation. However, whether learning-induced increases in ripple-spindle coupling are necessary for successful memory consolidation has not been tested directly. In order to decouple ripple-spindle oscillations, here we chemogenetically inhibited parvalbumin-positive (PV+) interneurons, since their activity is important for regulating the timing of spiking activity during oscillations. We found that contextual fear conditioning increased ripple-spindle coupling in mice. However, inhibition of PV+ cells in either CA1 or mPFC eliminated this learning-induced increase in ripple-spindle coupling without affecting ripple or spindle incidence. Consistent with the hypothesized importance of ripple-spindle coupling in memory consolidation, post-training inhibition of PV+ cells disrupted contextual fear memory consolidation. These results indicate that successful memory consolidation requires coherent hippocampal-neocortical communication mediated by PV+ cells., eLife digest Sleep contributes to the strengthening of memories. During non-dreaming sleep, neurons in regions of the brain that form and store memories – such as the hippocampus and prefrontal cortex – fire in rhythmic waves. The neurons in the hippocampus tend to fire during a wave that repeats up to 250 times per second, called sharp-wave ripples. Meanwhile, in the prefrontal cortex, the neurons tend to fire during a lower frequency wave that repeats 12 to 15 times per second, called spindles. During sleep and quiet wakefulness, hippocampal ripples often synchronize with prefrontal spindles; that is, both waves tend to occur at approximately the same time. Many neuroscientists think this allows the brain regions to better communicate with one another, which in turn should help the brain to strengthen memories. Consistent with this possibility, rodents that learn a new task show more synchrony between ripples and spindles afterwards. But no one had actually tested whether this increase in ripple-spindle synchrony does strengthen the rodent’s memory of the task. It was also unclear how the brain achieves such an increase. Xia et al. suspected that this process involved a group of inhibitory brain cells called parvalbumin-positive interneurons. These cells act like timekeepers, and help to synchronize the firing of groups of neurons. Xia et al. now show that training mice to associate an environment with a mild electric shock made it more likely that the animals would show ripple-spindle synchrony. Yet, inhibiting the activity of parvalbumin-positive interneurons in either the hippocampus or prefrontal cortex blocked this effect. It also prevented sleep from strengthening the animals’ memory of the link between the environment and the shock. Patients with Alzheimer’s disease have fewer parvalbumin-positive interneurons. By showing that these neurons help strengthen new memories, these findings may explain why losing them can impair memory. Restoring or replacing interneuron activity could be a promising therapeutic avenue to explore.

Memories are not static but continue to be processed after encoding. This is thought to allow the integration of related episodes via the identification of patterns. Although this idea lies at the heart of contemporary theories of systems consolidation, it has yet to be demonstrated experimentally. Using a modified water-maze paradigm in which platforms are drawn stochastically from a spatial distribution, we found that mice were better at matching platform distributions 30 d compared to 1 d after training. Post-training time-dependent improvements in pattern matching were associated with increased sensitivity to new platforms that conflicted with the pattern. Increased sensitivity to pattern conflict was reduced by pharmacogenetic inhibition of the medial prefrontal cortex (mPFC). These results indicate that pattern identification occurs over time, which can lead to conflicts between new information and existing knowledge that must be resolved, in part, by computations carried out in the mPFC.

Memories serve to establish some permanence to our inner lives despite the fleeting nature of subjective experience. Most neurobiological theories of memory assume that this mental permanence reflects an underlying cellular permanence. Namely, it is assumed that the cellular changes which first occur to store a memory are perpetuated for as long as the memory is stored. But is that really the case? In an opinion piece in this issue of Hippocampus, Aryeh Routtenberg raises the provocative idea that the subjective sense of memory persistence is not in fact a result of persistence at the cellular level, rather, that “supple synapses” and multiple “evanescent networks” that are forever changing are responsible for our memories. On one level, his proposal could be construed as a radical challenge to some of our most fundamental theories of the neurobiology of memory, including Donald Hebb's proposal that memories are stored by networks that strengthen their connections to increase the likelihood of the same activity patterns being recreated at a later date. However, it could also be seen as a moderating call, a call for a greater acknowledgement of the dynamic, stochastic, and distributed nature of neural networks. In this response to Routtenberg's article, we attempt to provide a clarification of the dividing line between these two interpretations of his argument, and in doing so, we provide some overview of the empirical evidence that bears on this subject. We argue that the data that exists to date favors the more moderate interpretation: that memory storage involves a process in which activity patterns are made more likely to reoccur, but that an under-appreciated reality is that mnemonic traces may continue to change and evolve over time. © 2013 Wiley Periodicals, Inc.

During the development of sensory systems, receptive fields are modified by stimuli in the environment. This is thought to rely on learning algorithms that are sensitive to correlations in spike timing between cells, but the manner in which developing circuits selectively exploit correlations that are related to sensory inputs is unknown. We recorded from neurons in the developing optic tectum of Xenopus laevis and found that repeated presentation of moving visual stimuli induced receptive field changes that reflected the properties of the stimuli and that this form of learning was disrupted when GABAergic transmission was blocked. Consistent with a role for spike timing-dependent mechanisms, GABA blockade altered spike-timing patterns in the tectum and increased correlations between cells that would affect plasticity at intratectal synapses. This is a previously unknown role for GABAergic signals in development and highlights the importance of regulating the statistics of spiking activity for learning.

Memory stabilization following encoding (synaptic consolidation) or memory reactivation (reconsolidation) requires gene expression and protein synthesis (Dudai and Eisenberg, 2004; Tronson and Taylor, 2007; Nader and Einarsson, 2010; Alberini, 2011). Although consolidation and reconsolidation may be mediated by distinct molecular mechanisms (Lee et al., 2004), disrupting the function of the transcription factor CREB impairs both processes (Kida et al., 2002; Mamiya et al., 2009). Phosphorylation of CREB at Ser133 recruits CREB binding protein (CBP)/p300 coactivators to activate transcription (Chrivia et al., 1993; Parker et al., 1996). In addition to this well known mechanism, CREB regulated transcription coactivators (CRTCs), previously called transducers of regulated CREB (TORC) activity, stimulate CREB-mediated transcription, even in the absence of CREB phosphorylation. Recently, CRTC1 has been shown to undergo activity-dependent trafficking from synapses and dendrites to the nucleus in excitatory hippocampal neurons (Ch'ng et al., 2012). Despite being a powerful and specific coactivator of CREB, the role of CRTC in memory is virtually unexplored. To examine the effects of increasing CRTC levels, we used viral vectors to locally and acutely increase CRTC1 in the dorsal hippocampus dentate gyrus region of mice before training or memory reactivation in context fear conditioning. Overexpressing CRTC1 enhanced both memory consolidation and reconsolidation; CRTC1-mediated memory facilitation was context specific (did not generalize to nontrained context) and long lasting (observed after virally expressed CRTC1 dissipated). CREB overexpression produced strikingly similar effects. Therefore, increasing CRTC1 or CREB function is sufficient to enhance the strength of new, as well as established reactivated, memories without compromising memory quality.

The retinotectal pathway of Xenopus laevis is a well-established experimental model for studying activity-dependent processes during visual system development. Such processes can be guided by stimulus-evoked activity patterns, which depend on the refractive characteristics of the eye. Previous work has shown that many animals are hyperopic at early developmental stages due to immature refractive properties. Whether this is also the case for Xenopus laevis is unknown. Here, we measure the focal length of the lens and the size of the eye of embryos at different stages and find that Xenopus laevis exhibits a similar shift from hyperopia to emmetropia. At early stages, immediately after innervation of the tectum by the optic nerve, Xenopus embryos are hyperopic. Soon afterwards the focal length of the lens decreases and the eye converges to a state of emmetropia. Despite being hyperopic we find that some visuospatial information is available to the young circuit. Calculations based on the optical properties of the eye show that even when the animals are hyperopic the blurred retinal image provides a crude spatial resolution. Furthermore, using whole-cell recordings in the optic tectum combined with visual stimulation through the intact eye, we show that tectal neurons in hyperopic embryos have spatially restricted glutamatergic receptive fields. Our data demonstrate that Xenopus laevis eyes undergo a process of developmental emmetropization, and suggest that despite an initial stage of suboptimal image formation there is potentially enough information to guide activity-dependent refinements of the retinotectal pathway from the onset of vision. © 2011 Wiley Periodicals, Inc. Develop Neurobiol 72: 507–519, 2012

Over the course of systems consolidation, there is a switch from a reliance on detailed episodic memories to generalized schematic memories. This switch is sometimes referred to as “memory transformation.” Here we demonstrate a previously unappreciated benefit of memory transformation, namely, its ability to enhance reinforcement learning in a dynamic environment. We developed a neural network that is trained to find rewards in a foraging task where reward locations are continuously changing. The network can use memories for specific locations (episodic memories) and statistical patterns of locations (schematic memories) to guide its search. We find that switching from an episodic to a schematic strategy over time leads to enhanced performance due to the tendency for the reward location to be highly correlated with itself in the short-term, but regress to a stable distribution in the long-term. We also show that the statistics of the environment determine the optimal utilization of both types of memory. Our work recasts the theoretical question of why memory transformation occurs, shifting the focus from the avoidance of memory interference toward the enhancement of reinforcement learning across multiple timescales.SIGNIFICANCE STATEMENTAs time passes, memories transform from a highly detailed state to a more gist-like state, in a process called “memory transformation.” Theories of memory transformation speak to its advantages in terms of reducing memory interference, increasing memory robustness, and building models of the environment. However, the role of memory transformation from the perspective of an agent that continuously acts and receives reward in its environment is not well explored. In this work, we demonstrate a view of memory transformation that defines it as a way of optimizing behavior across multiple timescales.

The objectives of this research were to further delineate the neural circuits subserving proposed memory-based behavioural subsystems in the hippocampal formation. These studies were guided by anatomical evidence showing a topographical organization of the hippocampal formation. Briefly, perpendicular to the medial/lateral entorhinal cortex division there is a second system of parallel circuits that separates the dorsal and ventral hippocampus. Recent work from this laboratory has provided evidence that the hippocampus incidentally encodes a context-specific inhibitory association during acquisition of a visual discrimination task. One question that emerges from this dataset is whether the dorsal or ventral hippocampus makes a unique contribution to this newly described function. Rats with neurotoxic lesions of the dorsal or ventral hippocampus were assessed on the acquisition of the visual discrimination task. Following asymptotic performance they were given reversal training in either the same or a different context from the original training. The results showed that the context-specific inhibition effect is mediated by a circuit that includes the ventral but not the dorsal hippocampus. Results from a control procedure showed that rats with either dorso-lateral striatum damage or dorsal hippocampal lesions were impaired on a tactile/spatial discrimination. Taken together, the results represent a double dissociation of learning and memory function between the ventral and dorsal hippocampus. The formation of an incidental inhibitory association was dependent on ventral but not dorsal hippocampal circuitry, and the opposite dependence was found for the spatial component of a tactile/spatial discrimination.

SummaryMemories are thought to be sparsely encoded in neuronal networks, but little is known about why a given neuron is recruited or allocated to a particular memory trace. Previous research shows that in the lateral amygdala (LA), neurons with increased CREB are selectively recruited to a fear memory trace. CREB is a ubiquitous transcription factor implicated in many cellular processes. Which process mediates neuronal memory allocation? One hypothesis is that CREB increases neuronal excitability to bias neuronal recruitment, although this has not been shown experimentally. Here we use several methods to increase neuronal excitability and show this both biases recruitment into the memory trace and enhances memory formation. Moreover, artificial activation of these neurons alone is a sufficient retrieval cue for fear memory expression, showing that these neurons are critical components of the memory trace. These results indicate that neuronal memory allocation is based on relative neuronal excitability immediately before training.Video Abstract

Forget It! When examining the relationship between the production of new neurons in the hippocampus and memory, studies have generally first manipulated hippocampal neurogenesis and afterward investigated memory formation and found that new neurons help to encode new memories. However, when investigating how similar manipulations of neurogenesis impact established hippocampus-dependent memories, Akers et al. (p. 598 ; see the Perspective by Mongiat and Schinder ) uncovered a role for neurogenesis in memory clearance. Thus, the continuous addition of new neurons both degrades existing information stored in hippocampal circuits and simultaneously provides substrates for new learning.