The construction of semantic memory: grammar-based representations learned from relational episodic information

Face familiarity detection with complex synapses

Synaptic plasticity is a complex phenomenon involving multiple biochemical processes that operate on different timescales. Complexity can greatly increase memory capacity when the variables characterizing the synaptic dynamics have limited precision, as shown in simple memory retrieval problems involving random patterns. Here we turn to a real-world problem, face familiarity detection, and we show that synaptic complexity can be harnessed to store in memory a large number of faces that can be recognized at a later time. The number of recognizable faces grows almost linearly with the number of synapses and quadratically with the number of neurons. Complex synapses outperform simple ones characterized by a single variable, even when the total number of dynamical variables is matched. Complex and simple synapses have distinct signatures that are testable in experiments. Our results indicate that a system with complex synapses can be used in real-world tasks such as face familiarity detection.

No evidence for a preferential role of sleep in episodic memory abstraction

Substantial evidence suggests that sleep has a role in declarative memory consolidation. An influential notion holds that such sleep-related memory consolidation is associated with a process of abstraction. The neural underpinnings of this putative process are thought to involve a hippocampo-neocortical dialogue. Specifically, the idea is that, during sleep, the statistical contingencies across episodes are re-coded to a less hippocampus-dependent format, while at the same time losing configural information. Two previous studies from our lab, however, failed to show a preferential role of sleep in either episodic memory decontextualisation or the formation of abstract knowledge across episodic exemplars. Rather these processes occurred over sleep and wake time alike. Here, we present two experiments that replicate and extend these previous studies and exclude some alternative interpretations. The combined data show that sleep has no preferential function in this respect. Rather, hippocampus-dependent memories are generalised to an equal extent across both wake and sleep time. The one point on which sleep outperforms wake is actually the preservation of episodic detail of memories stored prior to sleep.

Free recall scaling laws and short-term memory effects in a latching attractor network

Despite the complexity of human memory, paradigms like free recall have revealed robust qualitative and quantitative characteristics, such as power laws governing recall capacity. Although abstract random matrix models could explain such laws, the possibility of their implementation in large networks of interacting neurons has so far remained underexplored. We study an attractor network model of long-term memory endowed with firing rate adaptation and global inhibition. Under appropriate conditions, the transitioning behavior of the network from memory to memory is constrained by limit cycles that prevent the network from recalling all memories, with scaling similar to what has been found in experiments. When the model is supplemented with a heteroassociative learning rule, complementing the standard autoassociative learning rule, as well as short-term synaptic facilitation, our model reproduces other key findings in the free recall literature, namely, serial position effects, contiguity and forward asymmetry effects, and the semantic effects found to guide memory recall. The model is consistent with a broad series of manipulations aimed at gaining a better understanding of the variables that affect recall, such as the role of rehearsal, presentation rates, and continuous and/or end-of-list distractor conditions. We predict that recall capacity may be increased with the addition of small amounts of noise, for example, in the form of weak random stimuli during recall. Finally, we predict that, although the statistics of the encoded memories has a strong effect on the recall capacity, the power laws governing recall capacity may still be expected to hold.

Learning, memory and consolidation mechanisms for behavioral control in hierarchically organized cortico-basal ganglia systems

This article aims to provide a synthesis on the question how brain structures cooperate to accomplish hierarchically organized behaviors, characterized by low‐level, habitual routines nested in larger sequences of planned, goal‐directed behavior. The functioning of a connected set of brain structures—prefrontal cortex, hippocampus, striatum, and dopaminergic mesencephalon—is reviewed in relation to two important distinctions: (a) goal‐directed as opposed to habitual behavior and (b) model‐based and model‐free learning. Recent evidence indicates that the orbitomedial prefrontal cortices not only subserve goal‐directed behavior and model‐based learning, but also code the “landscape” (task space) of behaviorally relevant variables. While the hippocampus stands out for its role in coding and memorizing world state representations, it is argued to function in model‐based learning but is not required for coding of action–outcome contingencies, illustrating that goal‐directed behavior is not congruent with model‐based learning. While the dorsolateral and dorsomedial striatum largely conform to the dichotomy between habitual versus goal‐directed behavior, ventral striatal functions go beyond this distinction. Next, we contextualize findings on coding of reward‐prediction errors by ventral tegmental dopamine neurons to suggest a broader role of mesencephalic dopamine cells, viz. in behavioral reactivity and signaling unexpected sensory changes. We hypothesize that goal‐directed behavior is hierarchically organized in interconnected cortico‐basal ganglia loops, where a limbic‐affective prefrontal‐ventral striatal loop controls action selection in a dorsomedial prefrontal–striatal loop, which in turn regulates activity in sensorimotor‐dorsolateral striatal circuits. This structure for behavioral organization requires alignment with mechanisms for memory formation and consolidation. We propose that frontal corticothalamic circuits form a high‐level loop for memory processing that initiates and temporally organizes nested activities in lower‐level loops, including the hippocampus and the ripple‐associated replay it generates. The evidence on hierarchically organized behavior converges with that on consolidation mechanisms in suggesting a frontal‐to‐caudal directionality in processing control.

Shaping memory consolidation via targeted memory reactivation during sleep

Recent studies have shown that the reactivation of specific memories during sleep can be modulated using external stimulation. Specifically, it has been reported that matching a sensory stimulus (e.g., odor or sound cue) with target information (e.g., pairs of words, pictures, and motor sequences) during wakefulness, and then presenting the cue alone during sleep, facilitates memory of the target information. Thus, presenting learned cues while asleep may reactivate related declarative, procedural, and emotional material, and facilitate the neurophysiological processes underpinning memory consolidation in humans. This paradigm, which has been named targeted memory reactivation, has been successfully used to improve visuospatial and verbal memories, strengthen motor skills, modify implicit social biases, and enhance fear extinction. However, these studies also show that results depend on the type of memory investigated, the task employed, the sensory cue used, and the specific sleep stage of stimulation. Here, we present a review of how memory consolidation may be shaped using noninvasive sensory stimulation during sleep.

Four-hour delayed memory recall for stories: Theoretical and clinical implications of measuring accelerated long-term forgetting

It has been noted that clinical neuropsychological assessment is "blind" to certain abnormalities of consolidation that occur beyond standard 30-min delay intervals. For example, normal forgetting at 30-min delays has been followed by enhanced forgetting at longer delays in temporal-lobe epilepsy, termed accelerated long-term forgetting (ALF). To evaluate whether ALF could be identified in the neuropsychological assessment of a small sample of examinees with head injuries or other neurological diagnoses (n = 42), a 4-hr delayed recall condition was added to the Logical Memory subtest of the Wechsler Memory Scale-Third Edition. A small percentage of examinees (5/42 or 11%), despite exhibiting unimpaired story recall immediately and after 30-min delays, showed increased forgetting when compared with the average retention of stories (M = 0.83, SD = 0.17) after a 4-hr delay. Three of these 5 examinees also had impaired scores on 20-min delayed recall of the California Verbal Learning Test-Second Edition (CVLT-II) and would have been identified as having memory impairment without an extended, 4-hr delayed recall. In fact, the highest correlation among memory indexes was between 4-hr delayed recall of stories and delayed recall of the CVLT-II word list (r = .59, p < .0001), suggesting different consolidation rates for relational and nonrelational material.

Hippocampal sharp wave-ripple: A cognitive biomarker for episodic memory and planning

Sharp wave ripples (SPW-Rs) represent the most synchronous population pattern in the mammalian brain. Their excitatory output affects a wide area of the cortex and several subcortical nuclei. SPW-Rs occur during "off-line" states of the brain, associated with consummatory behaviors and non-REM sleep, and are influenced by numerous neurotransmitters and neuromodulators. They arise from the excitatory recurrent system of the CA3 region and the SPW-induced excitation brings about a fast network oscillation (ripple) in CA1. The spike content of SPW-Rs is temporally and spatially coordinated by a consortium of interneurons to replay fragments of waking neuronal sequences in a compressed format. SPW-Rs assist in transferring this compressed hippocampal representation to distributed circuits to support memory consolidation; selective disruption of SPW-Rs interferes with memory. Recently acquired and pre-existing information are combined during SPW-R replay to influence decisions, plan actions and, potentially, allow for creative thoughts. In addition to the widely studied contribution to memory, SPW-Rs may also affect endocrine function via activation of hypothalamic circuits. Alteration of the physiological mechanisms supporting SPW-Rs leads to their pathological conversion, "p-ripples," which are a marker of epileptogenic tissue and can be observed in rodent models of schizophrenia and Alzheimer's Disease. Mechanisms for SPW-R genesis and function are discussed in this review.

Hippocampal sharp-wave ripples in waking and sleeping states

Waking and sleeping states are privileged periods for distinct mnemonic processes. In waking behavior, rapid retrieval of previous experience aids memory-guided decision making. In sleep, a gradual series of reactivated associations supports consolidation of episodes into memory networks. Synchronized bursts of hippocampal place cells during events called sharp-wave ripples communicate associated neural patterns across distributed circuits in both waking and sleeping states. Differences between sleep and awake sharp-wave ripples, and in particular the accuracy of recapitulated experience, highlight their state-dependent roles in memory processes.

Internally generated sequences in learning and executing goal-directed behavior

A network of brain structures including hippocampus (HC), prefrontal cortex, and striatum controls goal-directed behavior and decision making. However, the neural mechanisms underlying these functions are unknown. Here, we review the role of 'internally generated sequences': structured, multi-neuron firing patterns in the network that are not confined to signaling the current state or location of an agent, but are generated on the basis of internal brain dynamics. Neurophysiological studies suggest that such sequences fulfill functions in memory consolidation, augmentation of representations, internal simulation, and recombination of acquired information. Using computational modeling, we propose that internally generated sequences may be productively considered a component of goal-directed decision systems, implementing a sampling-based inference engine that optimizes goal acquisition at multiple timescales of on-line choice, action control, and learning.

Brain networks shaping religious belief

We previously demonstrated with functional magnetic resonance imaging (fMRI) that religious belief depends upon three cognitive dimensions, which can be mapped to specific brain regions. In the present study, we considered these co-activated regions as nodes of three networks each one corresponding to a particular dimension, corresponding to each dimension and examined the causal flow within and between these networks to address two important hypotheses that remained untested in our previous work. First, we hypothesized that regions involved in theory of mind (ToM) are located upstream the causal flow and drive non-ToM regions, in line with theories attributing religion to the evolution of ToM. Second, we hypothesized that differences in directional connectivity are associated with differences in religiosity. To test these hypotheses, we performed a multivariate Granger causality-based directional connectivity analysis of fMRI data to demonstrate the causal flow within religious belief-related networks. Our results supported both hypotheses. Religious subjects preferentially activated a pathway from inferolateral to dorsomedial frontal cortex to monitor the intent and involvement of supernatural agents (SAs; intent-related ToM). Perception of SAs engaged pathways involved in fear regulation and affective ToM. Religious beliefs are founded both on propositional statements for doctrine, but also on episodic memory and imagery. Beliefs based on doctrine engaged a pathway from Broca's to Wernicke's language areas. Beliefs related to everyday life experiences engaged pathways involved in imagery. Beliefs implying less involved SAs and evoking imagery activated a pathway from right lateral temporal to occipital regions. This pathway was more active in non-religious compared to religious subjects, suggesting greater difficulty and procedural demands for imagining and processing the intent of SAs. Insights gained by Granger connectivity analysis inform us about the causal binding of individual regions activated during religious belief processing.

Long-term functional outcomes and correlation with regional brain connectivity by MRI diffusion tractography metrics in a near-term rabbit model of intrauterine growth restriction

BACKGROUND

Intrauterine growth restriction (IUGR) affects 5-10% of all newborns and is associated with increased risk of memory, attention and anxiety problems in late childhood and adolescence. The neurostructural correlates of long-term abnormal neurodevelopment associated with IUGR are unknown. Thus, the aim of this study was to provide a comprehensive description of the long-term functional and neurostructural correlates of abnormal neurodevelopment associated with IUGR in a near-term rabbit model (delivered at 30 days of gestation) and evaluate the development of quantitative imaging biomarkers of abnormal neurodevelopment based on diffusion magnetic resonance imaging (MRI) parameters and connectivity.

METHODOLOGY

At +70 postnatal days, 10 cases and 11 controls were functionally evaluated with the Open Field Behavioral Test which evaluates anxiety and attention and the Object Recognition Task that evaluates short-term memory and attention. Subsequently, brains were collected, fixed and a high resolution MRI was performed. Differences in diffusion parameters were analyzed by means of voxel-based and connectivity analysis measuring the number of fibers reconstructed within anxiety, attention and short-term memory networks over the total fibers.

PRINCIPAL FINDINGS

The results of the neurobehavioral and cognitive assessment showed a significant higher degree of anxiety, attention and memory problems in cases compared to controls in most of the variables explored. Voxel-based analysis (VBA) revealed significant differences between groups in multiple brain regions mainly in grey matter structures, whereas connectivity analysis demonstrated lower ratios of fibers within the networks in cases, reaching the statistical significance only in the left hemisphere for both networks. Finally, VBA and connectivity results were also correlated with functional outcome.

CONCLUSIONS

The rabbit model used reproduced long-term functional impairments and their neurostructural correlates of abnormal neurodevelopment associated with IUGR. The description of the pattern of microstructural changes underlying functional defects may help to develop biomarkers based in diffusion MRI and connectivity analysis.

Efficient partitioning of memory systems and its importance for memory consolidation

Long-term memories are likely stored in the synaptic weights of neuronal networks in the brain. The storage capacity of such networks depends on the degree of plasticity of their synapses. Highly plastic synapses allow for strong memories, but these are quickly overwritten. On the other hand, less labile synapses result in long-lasting but weak memories. Here we show that the trade-off between memory strength and memory lifetime can be overcome by partitioning the memory system into multiple regions characterized by different levels of synaptic plasticity and transferring memory information from the more to less plastic region. The improvement in memory lifetime is proportional to the number of memory regions, and the initial memory strength can be orders of magnitude larger than in a non-partitioned memory system. This model provides a fundamental computational reason for memory consolidation processes at the systems level.

Memory is critical to virtually all aspects of behavior, which may explain why memory is such a complex phenomenon involving numerous interacting mechanisms that operate across multiple brain regions. Many of these mechanisms cooperate to transform initially fragile memories into more permanent ones (memory consolidation). The process of memory consolidation starts at the level of individual synaptic connections, but it ultimately involves circuit reorganization in multiple brain regions. We show that there is a computational advantage in partitioning memory systems into subsystems that operate on different timescales. Individual subsystems cannot both store large amounts of information about new memories, and, at the same time, preserve older memories for long periods of time. Subsystems with highly plastic synapses (fast subsystems) are good at storing new memories but bad at retaining old ones, whereas subsystems with less plastic synapses (slow subsystems) can preserve old memories but cannot store detailed new memories. Here we propose a model of a multi-stage memory system that exhibits the good features of both its fast and its slow subsystems. Our model incorporates some of the important design principles of any memory system and allows us to interpret in a new way what we know about brain memory.

Aging memories: differential decay of episodic memory components

Some memories about events can persist for decades, even a lifetime. However, recent memories incorporate rich sensory information, including knowledge on the spatial and temporal ordering of event features, while old memories typically lack this "filmic" quality. We suggest that this apparent change in the nature of memories may reflect a preferential loss of hippocampus-dependent, configurational information over more cortically based memory components, including memory for individual objects. The current study systematically tests this hypothesis, using a new paradigm that allows the contemporaneous assessment of memory for objects, object pairings, and object-position conjunctions. Retention of each memory component was tested, at multiple intervals, up to 3 mo following encoding. The three memory subtasks adopted the same retrieval paradigm and were matched for initial difficulty. Results show differential decay of the tested episodic memory components, whereby memory for configurational aspects of a scene (objects' co-occurrence and object position) decays faster than memory for featured objects. Interestingly, memory requiring a visually detailed object representation decays at a similar rate as global object recognition, arguing against interpretations based on task difficulty and against the notion that (visual) detail is forgotten preferentially. These findings show that memories undergo qualitative changes as they age. More specifically, event memories become less configurational over time, preferentially losing some of the higher order associations that are dependent on the hippocampus for initial fast encoding. Implications for theories of long-term memory are discussed.

Structured cognition and neural systems: from rats to language

Much of animal and human cognition is compositional in nature: higher order, complex representations are formed by (rule-governed) combination of more primitive representations. We review here some of the evidence for compositionality in perception and memory, motivating an approach that takes ideas and techniques from computational linguistics to model aspects of structural representation in cognition. We summarize some recent developments in our work that, on the one hand, use algorithms from computational linguistics to model memory consolidation and the formation of semantic memory, and on the other hand use insights from the neurobiology of memory to develop a neurally inspired model of syntactic parsing that improves over existing (not cognitively motivated) models in computational linguistics. These two theoretical studies highlight interesting analogies between language acquisition, semantic memory and memory consolidation, and suggest possible neural mechanisms, implemented in computational algorithms that may underlie memory consolidation.