Distinguishing true versus illusory memories with brain imaging.

Kim and Cabeza show that true versus illusory memories held with high certainty depend on different neural mechanisms. Here is their abstract and one figure from the paper:

Although memory confidence and accuracy tend to be positively correlated, people sometimes remember with high confidence events that never happened. How can confidence correlate with accuracy but apply also to illusory memories? One possible explanation is that high confidence in veridical versus illusory memories depends on different neural mechanisms. The present study investigated this possibility using functional magnetic resonance imaging and a modified version of the Deese-Roediger-McDermott false-memory paradigm. Participants read short lists of categorized words, and brain activity was measured while they performed a recognition test with confidence rating. The study yielded three main findings. First, compared with low-confidence responses, high-confidence responses were associated with medial temporal lobe (MTL) activity in the case of true recognition but with frontoparietal activity in the case of false recognition. Second, these regions showed significant confidence-by-veridicality interactions. Finally, only MTL regions showed greater activity for high-confidence true recognition than for high-confidence false recognition, and only frontoparietal regions showed greater activity for high-confidence false recognition than for high-confidence true recognition. These findings indicate that confidence in true recognition is mediated primarily by a recollection-related MTL mechanism, whereas confidence in false recognition reflects mainly a familiarity-related frontoparietal mechanism. This account is consistent with the fuzzy trace theory of false recognition. Correlation analyses revealed that MTL and frontoparietal regions play complementary roles during episodic retrieval. In sum, the present study shows that when one focuses exclusively on high-confidence responses, the neural correlates of true and false memory are clearly different.

Figure: Activity within medial temporal lobes (A) was greater for high-confidence true recognition (HC-TR) than for high-confidence false recognition (HC-FR). Activity within a frontoparietal network (B) was greater for high-confidence false recognition than for high-confidence true recognition.

Single cells in monkey brain trained to associate numbers with their symbols

An interesting study from Diester and Nieder showing single nerve cell activity that might be the primitive cognitive precursor that ultimately has given rise to symbolic thinking in linguistic humans. Their abstract:

The utilization of symbols such as words and numbers as mental tools endows humans with unrivalled cognitive flexibility. In the number domain, a fundamental first step for the acquisition of numerical symbols is the semantic association of signs with cardinalities. We explored the primitives of such a semantic mapping process by recording single-cell activity in the monkey prefrontal and parietal cortices, brain structures critically involved in numerical cognition. Monkeys were trained to associate visual shapes with varying numbers of items in a matching task. After this long-term learning process, we found that the responses of many prefrontal neurons to the visual shapes reflected the associated numerical value in a behaviorally relevant way. In contrast, such association neurons were rarely found in the parietal lobe. These findings suggest a cardinal role of the prefrontal cortex in establishing semantic associations between signs and abstract categories, a cognitive precursor that may ultimately give rise to symbolic thinking in linguistic humans.

Emotional enhancement of memory and learning - a molecular mechanism.

Hu et al. have performed an interesting study of how the rush of noradrenaline during an emotional experience might enhance our ability to recall that experience. It causes a long term enhancement of the activity of nerve synapses using the neurotransmitter glutamate by stimulating the phosphorylation of a particular type of glutamate receptor. I'm afraid the molecular details will only make sense to those of you who know something about the chemistry of nerve transmission, but here they are, as outlined in the article's abstract:

Emotion enhances our ability to form vivid memories of even trivial events. Norepinephrine (NE), a neuromodulator released during emotional arousal, plays a central role in the emotional regulation of memory. However, the underlying molecular mechanism remains elusive. Toward this aim, we have examined the role of NE in contextual memory formation and in the synaptic delivery of GluR1-containing α-amino-3-hydroxy-5-methyl-4-isoxazoleproprionic acid (AMPA)-type glutamate receptors during long-term potentiation (LTP), a candidate synaptic mechanism for learning. We found that NE, as well as emotional stress, induces phosphorylation of GluR1 at sites critical for its synaptic delivery. Phosphorylation at these sites is necessary and sufficient to lower the threshold for GluR1 synaptic incorporation during LTP. In behavioral experiments, NE can lower the threshold for memory formation in wild-type mice but not in mice carrying mutations in the GluR1 phosphorylation sites. Our results indicate that NE-driven phosphorylation of GluR1 facilitates the synaptic delivery of GluR1-containing AMPARs, lowering the threshold for LTP, thereby providing a molecular mechanism for how emotion enhances learning and memory.

Genetic dissociation of multiple dopamine roles in learning

Here is the abstract of Frank et al., who show that three genetic variants of the dopamine systems that influence our reactions to positive and negative outcomes (and anticipations) have different effects on human reinforcement learning.

What are the genetic and neural components that support adaptive learning from positive and negative outcomes? Here, we show with genetic analyses that three independent dopaminergic mechanisms contribute to reward and avoidance learning in humans. A polymorphism in the DARPP-32 gene, associated with striatal dopamine function, predicted relatively better probabilistic reward learning. Conversely, the C957T polymorphism of the DRD2 gene, associated with striatal D2 receptor function, predicted the degree to which participants learned to avoid choices that had been probabilistically associated with negative outcomes. The Val/Met polymorphism of the COMT gene, associated with prefrontal cortical dopamine function, predicted participants' ability to rapidly adapt behavior on a trial-to-trial basis. These findings support a neurocomputational dissociation between striatal and prefrontal dopaminergic mechanisms in reinforcement learning. Computational maximum likelihood analyses reveal independent gene effects on three reinforcement learning parameters that can explain the observed dissociations.

A Memory Toolbox

A reader sends this link to 75 tips for going from amnesic to elephantic...

Parallel Distributed Processing and Semantic Cognition

Timothy T. Rogers and James L. McClelland have distilled the essence of the arguments in their book "Semantic Cognition: A Parallel Distributed Processing Approach" for an article (PDF here) to appear in Brain and Behavioral Sciences with peer commentary. Here is their abstract:

In our recent book, we present a parallel distributed processing theory of the acquisition, representation and use of human semantic knowledge. The theory proposes that semantic abilities arise from the flow of activation amongst simple, neuron-like processing units, as governed by the strengths of interconnecting weights; and that acquisition of new semantic information involves the gradual adjustment of weights in the system in response to experience. These simple ideas explain a wide range of empirical phenomena from studies of categorization, lexical acquisition, and disordered semantic cognition. In this précis we focus on phenomena central to the reaction against similarity-based theories that arose in the 1980's and that subsequently motivated the "theory-theory" approach to semantic knowledge. Specifically, we consider i) how concepts differentiate in early development, ii) why some groupings of items seem to form "good" or coherent categories while others do not, iii) why different properties seem central or important to different concepts, iv) why children and adults sometimes attest to beliefs that seem to contradict their direct experience, v) how concepts reorganize between the ages of 4 and 10, and vi) the relationship between causal knowledge and semantic knowledge. The explanations for these phenomena are illustrated with reference to a simple feed-forward connectionist model; and the relationship between this simple model, the broader theory, and more general issues in cognitive science are discussed.

Interactions between Declarative and Procedural Memories

Brown and Robertson do a simple experiment showing interaction between two main memory systems usually thought to be independent. Their abstract, slightly edited:

The acquisition of declarative (i.e., facts) and procedural (i.e., skills) memories may be supported by independent systems. This same organization may exist, after memory acquisition, when memories are processed off-line during consolidation. Alternatively, memory consolidation may be supported by interactive systems. This latter interactive organization predicts interference between declarative and procedural memories. Here, we show that procedural consolidation, expressed as an off-line motor skill improvement, can be blocked by declarative learning over wake, but not over a night of sleep. [note: the procedural task was learning a sequence of visually cued button presses at four possible postions.] The extent of the blockade on procedural consolidation was correlated to participants' declarative word recall. Similarly, in another experiment, the reciprocal relationship was found: declarative consolidation was blocked by procedural learning over wake, but not over a night of sleep. [note: The declarative task was learning a list of 16 words each individually presented on a computer screen for two seconds, with the list being presented in the same order five times.] The decrease in declarative recall was correlated to participants' procedural learning. These results challenge the concept of fixed independent memory systems; instead, they suggest a dynamic relationship, modulated by when consolidation takes place, allowing at times for a reciprocal interaction between memory systems.

The prospective brain

I've been meaning to point you to a nice review article by Daniel Schacter and colleagues (PDF here). Here is the abstract and a summary figure.

A rapidly growing number of recent studies show that imagining the future depends on much of the same neural machinery that is needed for remembering the past. These findings have led to the concept of the prospective brain; an idea that a crucial function of the brain is to use stored information to imagine, simulate and predict possible future events. We suggest that processes such as memory can be productively re-conceptualized in light of this idea.

The core brain system that is consistently activated while remembering the past, envisioning the future and during related forms of mental simulation is illustrated schematically. Prominent components of this network include medial prefrontal regions, posterior regions in the medial and lateral parietal cortex (extending into the precuneus and the retrosplenial cortex), the lateral temporal cortex and the medial temporal lobe. Moreover, regions within this core brain system are functionally correlated with each other and, prominently, with the hippocampal formation. We suggest that this core brain system functions adaptively to integrate information about relationships and associations from past experiences, in order to construct mental simulations about possible future events.

An acetylcholine receptor agonist improves cognition

The alpha-7 nicotinic acetylcholine receptor (nAChR) plays an important role in cognitive processes and may represent a drug target for treating cognitive deficits in neurodegenerative and psychiatric disorders. Bitner et al. study the effects of a particular AChR enhancer, or agonist, whose simple name is A-582941.

The figure shows the general structure of this class of molecules. A-582941 enhanced cognitive performance in behavioral assays including the monkey delayed matching-to-sample, rat social recognition, and mouse inhibitory avoidance models that capture domains of working memory, short-term recognition memory, and long-term memory consolidation, respectively. Their results demonstrate that alpha-7 nAChR agonism can lead to broad-spectrum efficacy in animal models at doses that enhance ERK1/2 (extracellular-signal regulated kinase) and CREB (cAMP response element-binding protein) phosphorylation/activation and may represent a mechanism that offers potential to improve cognitive deficits associated with neurodegenerative and psychiatric diseases, such as Alzheimer's disease and schizophrenia.

Brain correlates of different spatial learning strategies

Each of us tends to emphasize one of two main strategies for spacial navigation. Learning the relationships between environmental landmarks using a "spatial memory strategy" to construct a cognitive map depends on the hippocampus. Navigating using a "response strategy", or series of turns at precise decision points (turn left at corner, then turn right at...), involves the caudate nucleus and proceeds without using landmark relationships. Bohbot et al. have used a virtual maze task to examine 50 young healthy subjects, half reporting the use each strategy. Those using the spatial strategy

...had significantly more gray matter in the hippocampus and less gray matter in the caudate nucleus compared with response learners. Furthermore, the gray matter in the hippocampus was negatively correlated to the gray matter in the caudate nucleus, suggesting a competitive interaction between these two brain areas.

In a second analysis:

.. the gray matter of regions known to be anatomically connected to the hippocampus, such as the amygdala, parahippocampal, perirhinal, entorhinal and orbitofrontal cortices were shown to covary with gray matter in the hippocampus. Because low gray matter in the hippocampus is a risk factor for Alzheimer's disease, these results have important implications for intervention programs that aim at functional recovery in these brain areas. In addition, these data suggest that spatial strategies may provide protective effects against degeneration of the hippocampus that occurs with normal aging.

The decline of memory

J.L. Bader notes that Britney Spear's memory lapse while she was lip-synching during the recent MTV music video awards is a reflection of the general decline of dependence on memory in our culture. Why remember anything, when you can always google or wikipedia it; and all your contacts and phone numbers are stored in your cell phone? (And yes, I was one of the $200 beta testers of the Apple iPhone.) Some clips:

Oration and recitation, once staples of the American school system, have largely been phased out. Rhetoric programs at universities have narrowed, merged with communications departments, or been eliminated altogether...“We don’t have that kind of oral culture anymore,” said Prof. James Engell, author of “The Committed Word: Literature and Public Values,” who teaches a rhetoric course at Harvard. “We are in a culture that devalues our sense of memory.” Back when John Quincy Adams was teaching it, Mr. Engell said, “rhetoric was an umbrella where you got moral philosophy, the development of literary taste, intellectual prose, aesthetic appreciation, memorization and oral presentation. The ultimate object of this was what the Greeks called phronesis, or practical wisdom.”

...But contemporary scientists have discovered that memorization exercises can stave off dementia, introducing a new world of “neurobics.” Memory needs a workout as much as the abs do. Researchers have even shown that reciting poetry in dactylic hexameter can help synchronize heartbeats with breathing.

Roles of parietal and prefrontal cortex in working memory

Champod and Petrides distinguish monitoring and manipulation tasks carried out by working memory and demonstrate different brain correlates. Their abstract, and a figure:

Numerous functional neuroimaging studies reported increased activity in the middorsolateral prefrontal cortex (MDLFC) and the posterior parietal cortex (PPC) during the performance of working memory tasks. However, the role of the PPC in working memory is not understood and, although there is strong evidence that the MDLFC is involved in the monitoring of information in working memory, it is also often stated that it is involved in the manipulation of such information. This event-related functional magnetic resonance imaging study compared brain activity during the performance of working memory trials in which either monitoring or manipulation of information was required. The results show that the PPC is centrally involved in manipulation processes, whereas activation of the MDLFC is related to the monitoring of the information that is being manipulated. This study provides dissociation of activation in these two regions and, thus, succeeds in further specifying their relative contribution to working memory.

Figure: Activity in the manipulation minus monitoring and in the monitoring minus manipulation comparisons. Cortical surface renderings in standard stereotaxic space of a subject's brain are shown on the left. (a) Increased activity in the left IPS obtained from the manipulation minus monitoring comparison. The vertical blue line on the left hemisphere cortical surface rendering indicates the anteroposterior level of the coronal section illustrated on the right. (b) Increased activity in the right MDLFC obtained from the monitoring minus manipulation comparison. The vertical green line on the right hemisphere cortical surface rendering indicates the anteroposterior level of the coronal section illustrated on the right side. CS, central sulcus; PoCS, postcentral sulcus; PCS, precentral sulcus; SFS, superior frontal sulcus; IFS, inferior frontal sulcus; MFS, middle frontal sulcus.

Daytime sleep consolidates motor memory

Here is the abstract from Korman et al. :

Two behavioral phenomena characterize human motor memory consolidation: diminishing susceptibility to interference by a subsequent experience and the emergence of delayed, offline gains in performance. A recent model proposes that the sleep-independent reduction in interference is followed by the sleep-dependent expression of offline gains. Here, using the finger-opposition sequence–learning task, we show that an interference experienced at 2 h, but not 8 h, following the initial training prevented the expression of delayed gains at 24 h post-training. However, a 90-min nap, immediately post-training, markedly reduced the susceptibility to interference, with robust delayed gains expressed overnight, despite interference at 2 h post-training. With no interference, a nap resulted in much earlier expression of delayed gains, within 8 h post-training. These results suggest that the evolution of robustness to interference and the evolution of delayed gains can coincide immediately post-training and that both effects reflect sleep-sensitive processes.

And here is a graphic summarizing the results from the review by Diekelmann and Born:

Two ways of consolidating memory of finger tapping skill.
(a) Evolution of finger-to-thumb tapping skill under three experimental key conditions. From top to bottom: after training a specific sequence (Sequence A) in the morning and a first retest 8 h later, a distinct gain in performance developed at the second retest following overnight sleep (purple). Interference by training on a different sequence (Sequence B) 2 h after training of Sequence A completely abolished any sleep-dependent overnight gain developing between the first and second retest (blue). This overnight gain was restored when subjects napped for 90 min between training of Sequence A and interference training on Sequence B (green). (b) Model of skill memory consolidation. Representations of finger tapping skill are encoded in a temporary store. Stabilization (resistance to interference) of the representation can be achieved either through time-dependent synaptic consolidation (dark green) in the temporary buffer or through sleep-dependent system consolidation (red) that leads to a redistribution of the representation to different neuronal networks for long-term storage. Memory enhancement (delayed gains in performance) requires sleep-dependent system consolidation.

An enzyme that keeps old memories alive

Greg Miller writes a brief review of work by Shema et al. :

Many substances interfere with memory, as any hung-over partygoer can attest. But although booze and drugs can disrupt the making of new memories (such as the embarrassing antics at last night's party), they leave older memories intact. Neuroscientists think this is because, after a time, memories become wired into the brain in a way that makes them harder to wipe out: Long-term memories, in the generally accepted view, are maintained by structural changes to the synaptic connections between neurons.

The study [by Shama et al.] adds to other recent evidence that may challenge, or at least complicate, this view. A team of neuroscientists reports that injecting a drug that blocks an enzyme called protein kinase Mzeta (PKMzeta) into the cerebral cortex of rats makes the animals forget a meal that made them sick weeks earlier. The findings suggest that the continuing activity of PKMzeta is somehow necessary to maintain long-term memory, something that's not predicted by most current hypotheses on the mechanisms of memory. The work also hints at the possibility of future drugs that could tinker with memory--for therapeutic uses or for boosting brainpower.

"This is a somewhat mind-blowing conclusion," says David Glanzman, a neuroscientist at the University of California, Los Angeles. Enzymes similar to PKMzeta are known to be important in early stages of memory formation, Glanzman says, but most researchers had thought that these compounds were not needed to sustain memory once synaptic changes--such as the growth of new synapses or the strengthening of existing ones--had occurred.

...Going forward, it will be important to figure out how specific ZIP's memory-erasing effects are, says Lynn Nadel, a neuroscientist at the University of Arizona in Tucson. "It's possible that ZIP erases all learning, no matter how old," Nadel says. But if the drug works more selectively, it could one day have clinical applications, he says. For example, researchers and clinicians have been looking for compounds capable of eliminating the painful memories of trauma survivors (Science, 2 April 2004, p. 34). The flip side is cognitive enhancement, adds Richard Morris, a neuroscientist at the University of Edinburgh, U.K. "The next step might be to find out whether augmenting the action of PKMzeta can help sustain memories for longer than occurs normally."

Genetic changes that influence memory

Mery et al. show that a natural genetic polymorphism influences short versus long term memory in fruit flies. You can extract the basic message from their abstract, passing over the molecular details if that's not your gig:

Knowing which genes contribute to natural variation in learning and memory would help us understand how differences in these cognitive traits evolve among populations and species. We show that a natural polymorphism at the foraging (for) locus, which encodes a cGMP-dependent protein kinase (PKG), affects associative olfactory learning in Drosophila melanogaster. In an assay that tests the ability to associate an odor with mechanical shock, flies homozygous for one natural allelic variant of this gene (forR) showed better short-term but poorer long-term memory than flies homozygous for another natural allele (fors). The fors allele is characterized by reduced PKG activity. We showed that forR-like levels of both short-term learning and long-term memory can be induced in fors flies by selectively increasing the level of PKG in the mushroom bodies, which are centers of olfactory learning in the fly brain. Thus, the natural polymorphism at for may mediate an evolutionary tradeoff between short- and long-term memory. The respective strengths of learning performance of the two genotypes seem coadapted with their effects on foraging behavior: forR flies move more between food patches and so could particularly benefit from fast learning, whereas fors flies are more sedentary, which should favor good long-term memory.

Novel environments stimulate memory molecules

Remembering something requires changes in how our nerve cells talk to each other, and a process called long termed potentiation, or LTP, is regarded as a good model for one such underlying change. LTP refers to an enhancement of the synapse between two nerve cells such that an action potential arriving in a presynaptic terminal causes a larger voltage change in the postsynaptic terminal. This process is thought to require the synthesis of new proteins in the synapse and is essential in establishing long term memories(LTM). Moncada and Viola have made the interesting observation that weak inhibitory avoidance training, which induces short- but not long-term memory (LTM), can be consolidated into LTM by an exploration to a novel, but not a familiar, environment occurring close in time to the training session. "This memory-promoting effect caused by novelty depends on activation of dopamine D1/D5 receptors and requires newly synthesized proteins in the dorsal hippocampus. The results indicate the existence of a behavioral tagging process in which the exploration to a novel environment provides the plasticity-related proteins to stabilize the inhibitory avoidance memory trace."

Suppression of emotional memories.

Here is the abstract from Depre et al.'s article (PDF here):

Whether memories can be suppressed has been a controversial issue in psychology and cognitive neuroscience for decades. We found evidence that emotional memories are suppressed via two time-differentiated neural mechanisms: (i) an initial suppression by the right inferior frontal gyrus over regions supporting sensory components of the memory representation (visual cortex, thalamus), followed by (ii) right medial frontal gyrus control over regions supporting multimodal and emotional components of the memory representation (hippocampus, amygdala), both of which are influenced by fronto-polar regions. These results indicate that memory suppression does occur and, at least in nonpsychiatric populations, is under the control of prefrontal regions.

They used used a Think/No-Think paradigm (T/NT) in which individuals attempt to elaborate a memory by repetitively thinking of it (T condition) or to suppress a memory by repetitively not letting it enter consciousness (NT condition).

Fig. 1. (A) Experimental procedure. Individuals were first trained during structural scanning to associate 40 cue-target pairs. During the experimental phase, brain activity was recorded using fMRI while individuals viewed only the face (16 faces per condition, 12 repetitions per face; 3.5 s per face). On some trials they were instructed to think of the previously learned picture; on other trials they were instructed not to let the previously associated picture enter consciousness. The presentation of only the cue (i.e., the face) ensures that individuals manipulate the memory of the target picture. The additional faces (8 items) not shown during this phase acted as a behavioral baseline. During the test phase, the individuals were shown the 40 faces and asked to describe the previously associated picture. (B) Behavioral results: percentage recall for each participant for T trials (green) and NT trials (red), with the dotted line indicating baseline recall for items not viewed in the experimental phase.

Fig. 2. Functional activation of brain areas involved in (A) cognitive control, (B) sensory representations of memory, and (C) memory processes and emotional components of memory (rSFG, right superior frontal gyrus; rMFG, right middle frontal gyrus; rIFG, right inferior frontal gyrus; Pul, pulvinar; FG, fusiform gyrus; Hip, hippocampus; Amy, amygdala). Red indicates greater activity for NT trials than for T trials; blue indicates the reverse. Conjunction analyses revealed that areas seen in blue are the culmination of increased activity for T trials above baseline as well as decreased activity of NT trials below baseline.

Here is the last portion of their discussion:

At a broader level, our findings extend research suggesting that prefrontal brain areas associated with inhibitory mechanisms (BA 10 and superior, inferior, and middle FG) are lateralized predominantly to the right hemisphere. We have shown the involvement of these areas in the suppression of emotional memories, which replicates current literature suggesting that these areas are active in the suppression of emotional reactivity. Activity in these brain areas, along with inhibition over Hip and Amy, suggests that suppression of emotional memories may use mechanisms similar to those used in emotion regulation. Thus, various right-lateralized PFC areas may be involved in coordinating suppression processes across many behavioral domains, including memory retrieval, motor processes, feelings of social rejection, self motives, and state emotional reactivity.

Our findings may have implications for therapeutic approaches to disorders involving the inability to suppress emotionally distressing memories and thoughts, including PTSD, phobias, ruminative depression/anxiety, and OCD. They provide the possibility for approaches to controlling memories by suppressing sensory aspects of memory and/or by strengthening cognitive control over memory and emotional processes through repeated practice. Refinement of therapeutic procedures based on these distinct means of manipulating emotional memory might be an exciting and fruitful development in future clinical research.

Our results suggest that effective voluntary suppression of emotional memory only develops with repeated attempts to cognitively control posterior brain areas underlying instantiated memories. In this sense, memory suppression may best be conceived as a dynamic process in which the brain acquires multiple modulatory influences to reduce the likelihood of retrieving unwanted memories.

Remembering small pattern differences.

Bannerman and Sprengel discuss (PDF here) and offer perspective on work of McHugh et al. from Tonegawa's laboratory showing synaptic details of how the mouse hippocampus carries out pattern separation. The findings explain how we detect small changes in our environment, perhaps allowing us to update and guide our choices. They offer a nice graphic of the hippocampus, which is central in this processes.

Knowing what, when, and where. In the mouse brain, the dentate gyrus region of the hippocampus can detect small changes in the animal's spatial environment and differentiate between recent experiences that occur in the same place. The white arrows trace a path of signaling between different regions of the hippocampus. Sensory information can enter the hippocampus from the entorhinal cortex and is sent back to the entorhinal cortex after processing.

Ambiguity and anxiety: overreaction and a serotonin receptor

Nader and Alleine describe work of Tsetsenis et al.

When the threat of terrorist attack is elevated, the United States Department of Homeland Security changes its prediction of danger from yellow to orange to red. Most of us can manage our levels of vigilance and of anxiety appropriately in response to these cues. However, imagine how debilitating it would be if you were unable to manage your anxiety and reduce your fear of attack when the threat level was reduced. In fact, many people with anxiety disorders suffer from precisely this kind of condition. The paper by Tsetsenis et al. finds that mice lacking the serotonin 1a receptor overreact to ambiguous predictors of aversive events in this same way, providing insight into factors that could predispose individuals to such disorders and into the neural locus of the effect.

Understanding the neural bases of contingency is not simply an academic question, but very much a mental health one. Unpredictable aversive events can be much more stressful than the same events when they are anticipated. In addition, psychopathologies can influence the perception of contingency. For example, depressed people have a different sense than nondepressed people of how their responses affect the environment, and exposure to unpredictable or uncontrollable aversive events is suggested to directly influence the development of depression.

The new study by Tsetsenis et al. makes a significant contribution to our understanding of the neural mechanisms mediating contingency learning. The authors studied mice in which the serotonin 1a receptor (Ht1a) gene was knocked out or inactivated during development. This receptor causes membrane hyperpolarization of nonserotonergic neurons and acts as an autoreceptor on serotonergic neurons in the raphe. Ht1a dysfunction is linked to anxiety disorders and depression, and mice lacking Ht1a receptors show increased avoidance behavior. This phenotype is attributable to the absence of the Ht1a in the forebrain during development; eliminating these receptors during adulthood does not cause the mice to show the anxious phenotype. Although fear of an aversive context is comparable in knockout and wild-type mice, the knockout mice over-generalize their fear of the 'aversive' context to a similar context containing novel elements, a situation in which wild-type mice are able to decrease their fear levels11. This finding suggested that these mutant mice focus unduly on cues that have been paired with shock rather than on cues that have not.

Figure: Humans and other animals can accurately estimate the probability of danger from their experience of specific environments or cues and use this information to respond appropriately. A normal mouse (top) accurately estimates the threat from an ambiguous cue, a sleeping cat, and a less ambiguous cue, an alert cat, and is appropriately cautious or alarmed, respectively. In contrast, anxious people and animals, such as the Htr1a knockout mouse assessed by Tsetsenis et al. (bottom), often overestimate the danger represented by ambiguous cues and over-respond, given the level of threat. This is likely to interfere with the need to respond to other important events in the environment (such as cheese).

Here is the abstract from Tsetsenis et al.

Serotonin receptor 1A knockout (Htr1aKO) mice show increased anxiety-related behavior in tests measuring innate avoidance. Here we demonstrate that Htr1aKO mice show enhanced fear conditioning to ambiguous conditioned stimuli, a hallmark of human anxiety. To examine the involvement of specific forebrain circuits in this phenotype, we developed a pharmacogenetic technique for the rapid tissue- and cell type–specific silencing of neural activity in vivo. Inhibition of neurons in the central nucleus of the amygdala suppressed conditioned responses to both ambiguous and nonambiguous cues. In contrast, inhibition of hippocampal dentate gyrus granule cells selectively suppressed conditioned responses to ambiguous cues and reversed the knockout phenotype. These data demonstrate that Htr1aKO mice have a bias in the processing of threatening cues that is moderated by hippocampal mossy-fiber circuits, and suggest that the hippocampus is important in the response to ambiguous aversive stimuli.

New steps in memory consolidation

Paz et al show how the hippocampal-medial prefrontal cortex interactions thought to support memory consolidation are enhanced by correlated activities in regions around the hippocampus. Their introduction gives a quick summary of known steps in memory consolidation which provides context for their experiment, here are some edited clips:

The hippocampus plays a time-limited role in the formation of declarative memories, with memories gradually becoming independent of the hippocampus over time. It is believed that these remote memories are gradually transferred from the hippocampus to the neocortex for long-term storage..investigations indicate that the medial prefrontal cortex (mPFC) is critical for the consolidation of hippocampal-dependent memories. In trace-conditioning tasks for instance, hippocampal lesions cause a severe deficit when made soon after training, but not after a month, whereas mPFC lesions produce the opposite pattern of impairments. ...The role of mPFC activity in memory formation remains unclear. One possibility is that mPFC affects the transfer of hippocampal activity toward the neocortex. Consistent with this possibility, the mPFC projects to the rhinal cortices, the main route for impulse traffic into and out of the hippocampus...the present study was undertaken to test the idea that the mPFC influences memory formation by modulating interactions between the neocortex and hippocampus at the level of the rhinal cortices. To this end, we examined the relative timing of unit activity in the mPFC, PR, and ER cortices during the acquisition of a trace-conditioning task.

And, here is the abstract of the paper:

Much data suggests that hippocampal–medial prefrontal cortex (mPFC) interactions support memory consolidation. This process is thought to involve the gradual transfer of transient hippocampal-dependent memories to distributed neocortical sites for long-term storage. However, hippocampal projections to the neocortex involve a multisynaptic pathway that sequentially progresses through the entorhinal and perirhinal regions before reaching the neocortex. Similarly, the mPFC influences the hippocampus via the rhinal cortices, suggesting that the rhinal cortices occupy a strategic position in this network. The present study thus tested the idea that the mPFC supports memory by facilitating the transfer of hippocampal activity to the neocortex via an enhancement of entorhinal to perirhinal communication. To this end, we simultaneously recorded mPFC, perirhinal, and entorhinal neurons during the acquisition of a trace-conditioning task in which a visual conditioned stimulus (CS) was followed by a delay period after which a liquid reward was administered. At learning onset, correlated perirhinal-entorhinal firing increased in relation to mPFC activity, but with no preferential directionality, and only after reward delivery. However, as learning progressed across days, mPFC activity gradually enhanced rhinal correlations in relation to the CS as well, and did so in a specific direction: from entorhinal to perirhinal neurons. This suggests that, at late stages of learning, mPFC activity facilitates entorhinal to perirhinal communication. Because this connection is a necessary step for the transfer of hippocampal activity to the neocortex, our results suggest that the mPFC is involved in the slow iterative process supporting the integration of hippocampal-dependent memories into neocortical networks.