Short-term memory trace in rapidly adapting synapses of inferior temporal cortex

Visual short-term memory tasks depend upon both the inferior temporal cortex (ITC) and the prefrontal cortex (PFC). Activity in some neurons persists after the first (sample) stimulus is shown. This delay-period activity has been proposed as an important mechanism for working memory. In ITC neurons, intervening (nonmatching) stimuli wipe out the delay-period activity; hence, the role of ITC in memory must depend upon a different mechanism. Here, we look for a possible mechanism by contrasting memory effects in two architectonically different parts of ITC: area TE and the perirhinal cortex. We found that a large proportion (80%) of stimulus-selective neurons in area TE of macaque ITCs exhibit a memory effect during the stimulus interval. During a sequential delayed matching-to-sample task (DMS), the noise in the neuronal response to the test image was correlated with the noise in the neuronal response to the sample image. Neurons in perirhinal cortex did not show this correlation. These results led us to hypothesize that area TE contributes to short-term memory by acting as a matched filter. When the sample image appears, each TE neuron captures a static copy of its inputs by rapidly adjusting its synaptic weights to match the strength of their individual inputs. Input signals from subsequent images are multiplied by those synaptic weights, thereby computing a measure of the correlation between the past and present inputs. The total activity in area TE is sufficient to quantify the similarity between the two images. This matched filter theory provides an explanation of what is remembered, where the trace is stored, and how comparison is done across time, all without requiring delay period activity. Simulations of a matched filter model match the experimental results, suggesting that area TE neurons store a synaptic memory trace during short-term visual memory.     

The Positional-Specificity Effect Reveals a Passive-Trace Contribution to Visual Short-Term Memory

The positional-specificity effect refers to enhanced performance in visual short-term memory (VSTM) when the recognition probe is presented at the same location as had been the sample, even though location is irrelevant to the match/nonmatch decision. We investigated the mechanisms underlying this effect with behavioral and fMRI studies of object change-detection performance. To test whether the positional-specificity effect is a direct consequence of active storage in VSTM, we varied memory load, reasoning that it should be observed for all objects presented in a sub-span array of items. The results, however, indicated that although robust with a memory load of 1, the positional-specificity effect was restricted to the second of two sequentially presented sample stimuli in a load-of-2 experiment. An additional behavioral experiment showed that this disruption wasn’t due to the increased load per se, because actively processing a second object – in the absence of a storage requirement – also eliminated the effect. These behavioral findings suggest that, during tests of object memory, position-related information is not actively stored in VSTM, but may be retained in a passive tag that marks the most recent site of selection. The fMRI data were consistent with this interpretation, failing to find location-specific bias in sustained delay-period activity, but revealing an enhanced response to recognition probes that matched the location of that trial’s sample stimulus.     

Microstimulation of frontal cortex can reorder a remembered spatial sequence

Complex goal-directed behaviors extend over time and thus depend on the ability to serially order memories and assemble compound, temporally coordinated movements. Theories of sequential processing range from simple associative chaining to hierarchical models in which order is encoded explicitly and separately from sequence components. To examine how short-term memory and planning for sequences might be coded, we used microstimulation to perturb neural activity in the supplementary eye field (SEF) while animals held a sequence of two cued locations in memory over a short delay. We found that stimulation affected the order in which animals saccaded to the locations, but not the memory for which locations were cued. These results imply that memory for sequential order can be dissociated from that of its components. Furthermore, stimulation of the SEF appeared to bias sequence endpoints to converge toward a location in contralateral space, suggesting that this area encodes sequences in terms of their endpoints rather than their individual components.     

Understanding the physical basis of memory: Molecular mechanisms of the engram

Memory, defined as the storage and use of learned information in the brain, is necessary to modulate behavior and critical for animals to adapt to their environments and survive. Despite being a cornerstone of brain function, questions surrounding the molecular and cellular mechanisms of how information is encoded, stored, and recalled remain largely unanswered. One widely held theory is that an engram is formed by a group of neurons that are active during learning, which undergoes biochemical and physical changes to store information in a stable state, and that are later reactivated during recall of the memory. In the past decade, the development of engram labeling methodologies has proven useful to investigate the biology of memory at the molecular and cellular levels. Engram technology allows the study of individual memories associated with particular experiences and their evolution over time, with enough experimental resolution to discriminate between different memory processes: learning (encoding), consolidation (the passage from short-term to long-term memories), and storage (the maintenance of memory in the brain). Here, we review the current understanding of memory formation at a molecular and cellular level by focusing on insights provided using engram technology.     

Spike-Timing Theory of Working Memory

Working memory (WM) is the part of the brain''s memory system that provides temporary storage and manipulation of information necessary for cognition. Although WM has limited capacity at any given time, it has vast memory content in the sense that it acts on the brain''s nearly infinite repertoire of lifetime long-term memories. Using simulations, we show that large memory content and WM functionality emerge spontaneously if we take the spike-timing nature of neuronal processing into account. Here, memories are represented by extensively overlapping groups of neurons that exhibit stereotypical time-locked spatiotemporal spike-timing patterns, called polychronous patterns; and synapses forming such polychronous neuronal groups (PNGs) are subject to associative synaptic plasticity in the form of both long-term and short-term spike-timing dependent plasticity. While long-term potentiation is essential in PNG formation, we show how short-term plasticity can temporarily strengthen the synapses of selected PNGs and lead to an increase in the spontaneous reactivation rate of these PNGs. This increased reactivation rate, consistent with in vivo recordings during WM tasks, results in high interspike interval variability and irregular, yet systematically changing, elevated firing rate profiles within the neurons of the selected PNGs. Additionally, our theory explains the relationship between such slowly changing firing rates and precisely timed spikes, and it reveals a novel relationship between WM and the perception of time on the order of seconds.     

Basic mechanisms for graded persistent activity: discrete attractors,continuous attractors,and dynamic representations

Persistent neural activity is observed in many systems, and is thought to be a neural substrate for holding memories over time delays of a few seconds. Recent work has addressed two issues. First, how can networks of neurons robustly hold such an active memory? Computer systems obtain significant robustness to noise by approximating analogue quantities with discrete digital representations. In a similar manner, theoretical models of persistent activity in spiking neurons have shown that the most robust and stable way to store the short-term memory of a continuous parameter is to approximate it with a discrete representation. This general idea applies very broadly to mechanisms that range from biochemical networks to single cells and to large circuits of neurons. Second, why is it commonly observed that persistent activity in the cortex can be strongly time-varying? This observation is almost ubiquitous, and therefore must be taken into account in our models and our understanding of how short-term memories are held in the cortex.     

Cannabinoid inhibition improves memory in food-storing birds, but with a cost

Food-storing birds demonstrate remarkable memory ability in recalling the locations of thousands of hidden food caches. Although this behaviour requires the hippocampus, its synaptic mechanisms are not understood. Here we show the effects of cannabinoid receptor (CB1-R) blockade on spatial memory in food-storing black-capped chickadees (Poecile atricapilla). Intra-hippocampal infusions of the CB1-R antagonist SR141716A enhanced long-term memory for the location of a hidden food reward, measured 72 h after encoding. However, when the reward location changed during the retention interval, birds that had received SR141716A during initial learning showed impairments in recalling the most recent reward location. Thus, blocking CB1-R activity may lead to more robust, long-lasting memories, but these memories may be a source of proactive interference. The relationship between trace strength and interference may be important in understanding neural mechanisms of hippocampal function in general, as well as understanding the enhanced memory of food-storing birds.     

The Astrocentric Hypothesis: proposed role of astrocytes in consciousness and memory formation.

Consciousness is self-awareness. This process is closely associated with attention and working memory, a special form of short-term memory, which is vital when solving explicit task. Edelman has equated consciousness as the "remembered present" to highlight the importance of this form of memory (G.M. Edelman, Bright Air, Brilliant Fire, Basic Books, New York, 1992). The majority of other memories are recollections of past events that are encoded, stored, and brought back into consciousness if appropriate for solving new problems. Encoding prior experiences into memories is based on the salience of each event (A.R. Damasio, Descartes' Error, G.P. Putnam's Sons, New York, 1994; G.M. Edelman, Bright Air, Brilliant Fire, Basic Books, New York, 1992). It is proposed that protoplasmic astrocytes bind attended sensory information into consciousness and store encoded memories. This conclusion is supported by research conducted by gliobiologist over the past 15 years.     

A Model of Visuospatial Working Memory in Prefrontal Cortex: Recurrent Network and Cellular Bistability

We report a computer simulation of the visuospatial delayed-response experiments of Funahashi et al. (1989), using a firing-rate model that combines intrinsic cellular bistability with the recurrent local network architecture of the neocortex. In our model, the visuospatial working memory is stored in the form of a continuum of network activity profiles that coexist with a spontaneous activity state. These neuronal firing patterns provide a population code for the cue position in a graded manner. We show that neuronal persistent activity and tuning curves of delay-period activity (memory fields) can be generated by an excitatory feedback circuit and recurrent synaptic inhibition. However, if the memory fields are constructed solely by network mechanisms, noise may induce a random drift over time in the encoded cue position, so that the working memory storage becomes unreliable. Furthermore, a distraction stimulus presented during the delay period produces a systematic shift in the encoded cue position. We found that the working memory performance can be rendered robust against noise and distraction stimuli if single neurons are endowed with cellular bistability (presumably due to intrinsic ion channel mechanisms) that is conditional and realized only with sustained synaptic inputs from the recurrent network. We discuss how cellular bistability at the single cell level may be detected by analysis of spike trains recorded during delay-period activity and how local modulation of intrinsic cell properties and/or synaptic transmission can alter the memory fields of individual neurons in the prefrontal cortex.     

Structural Synaptic Plasticity Has High Memory Capacity and Can Explain Graded Amnesia,Catastrophic Forgetting,and the Spacing Effect

Although already William James and, more explicitly, Donald Hebb''s theory of cell assemblies have suggested that activity-dependent rewiring of neuronal networks is the substrate of learning and memory, over the last six decades most theoretical work on memory has focused on plasticity of existing synapses in prewired networks. Research in the last decade has emphasized that structural modification of synaptic connectivity is common in the adult brain and tightly correlated with learning and memory. Here we present a parsimonious computational model for learning by structural plasticity. The basic modeling units are “potential synapses” defined as locations in the network where synapses can potentially grow to connect two neurons. This model generalizes well-known previous models for associative learning based on weight plasticity. Therefore, existing theory can be applied to analyze how many memories and how much information structural plasticity can store in a synapse. Surprisingly, we find that structural plasticity largely outperforms weight plasticity and can achieve a much higher storage capacity per synapse. The effect of structural plasticity on the structure of sparsely connected networks is quite intuitive: Structural plasticity increases the “effectual network connectivity”, that is, the network wiring that specifically supports storage and recall of the memories. Further, this model of structural plasticity produces gradients of effectual connectivity in the course of learning, thereby explaining various cognitive phenomena including graded amnesia, catastrophic forgetting, and the spacing effect.     

Effect of anoxic/aerobic phase fraction on N2O emission in a sequencing batch reactor under low temperature

Laboratory scale anoxic/aerobic sequencing batch reactor (A/O SBR) was operated around 15 °C to evaluate the effect of anoxic/aerobic phase fraction (PF) on N₂O emission. The ammonia removal exhibited a decrease trend with the increase of PF, while the highest total nitrogen removal was achieved at PF = 0.5. Almost all the N₂O was emitted during the aerobic phase, despite of the PF value. However, the net emission of N₂O was affected by PF. Under the premise of completely aerobic nitrification, the lowest N₂O emission was achieved at PF = 0.5, with a N₂O-N conversion rate of 9.8%. At lower PF (PF = 0.2), N₂O emission was stimulated by residual nitrite caused by uncompleted denitrification during the anoxic phase. On the other hand, the exhaustion of the easily degradable carbon was the major cause for the high N₂O emission at higher PF (PF = 0.5). The N₂O emission increased with the decreasing temperature. The time-weighted N₂O emission quantity at 15 °C was 2.9 times higher than that at 25 °C.     

Nitric oxide regulates input specificity of long-term depression and context dependence of cerebellar learning

Recent studies have shown that multiple internal models are acquired in the cerebellum and that these can be switched under a given context of behavior. It has been proposed that long-term depression (LTD) of parallel fiber (PF)–Purkinje cell (PC) synapses forms the cellular basis of cerebellar learning, and that the presynaptically synthesized messenger nitric oxide (NO) is a crucial “gatekeeper” for LTD. Because NO diffuses freely to neighboring synapses, this volume learning is not input-specific and brings into question the biological significance of LTD as the basic mechanism for efficient supervised learning. To better characterize the role of NO in cerebellar learning, we simulated the sequence of electrophysiological and biochemical events in PF–PC LTD by combining established simulation models of the electrophysiology, calcium dynamics, and signaling pathways of the PC. The results demonstrate that the local NO concentration is critical for induction of LTD and for its input specificity. Pre- and postsynaptic coincident firing is not sufficient for a PF–PC synapse to undergo LTD, and LTD is induced only when a sufficient amount of NO is provided by activation of the surrounding PFs. On the other hand, above-adequate levels of activity in nearby PFs cause accumulation of NO, which also allows LTD in neighboring synapses that were not directly stimulated, ruining input specificity. These findings lead us to propose the hypothesis that NO represents the relevance of a given context and enables context-dependent selection of internal models to be updated. We also predict sparse PF activity in vivo because, otherwise, input specificity would be lost.     

Place Cells,Grid Cells,and Memory

The hippocampal system is critical for storage and retrieval of declarative memories, including memories for locations and events that take place at those locations. Spatial memories place high demands on capacity. Memories must be distinct to be recalled without interference and encoding must be fast. Recent studies have indicated that hippocampal networks allow for fast storage of large quantities of uncorrelated spatial information. The aim of the this article is to review and discuss some of this work, taking as a starting point the discovery of multiple functionally specialized cell types of the hippocampal–entorhinal circuit, such as place, grid, and border cells. We will show that grid cells provide the hippocampus with a metric, as well as a putative mechanism for decorrelation of representations, that the formation of environment-specific place maps depends on mechanisms for long-term plasticity in the hippocampus, and that long-term spatiotemporal memory storage may depend on offline consolidation processes related to sharp-wave ripple activity in the hippocampus. The multitude of representations generated through interactions between a variety of functionally specialized cell types in the entorhinal–hippocampal circuit may be at the heart of the mechanism for declarative memory formation.The scientific study of human memory started with Herman Ebbinghaus, who initiated the quantitative investigation of associative memory processes as they take place (Ebbinghaus 1885). Ebbinghaus described the conditions that influence memory formation and he determined several basic principles of encoding and recall, such as the law of frequency and the effect of time on forgetting. With Ebbinghaus, higher mental functions were brought to the laboratory. In parallel with the human learning tradition that Ebbinghaus started, a new generation of experimental psychologists described the laws of associative learning in animals. With behaviorists like Pavlov, Watson, Hull, Skinner, and Tolman, a rigorous program for identifying the laws of animal learning was initiated. By the middle of the 20th century, a language for associative learning processes had been developed, and many of the fundamental relationships between environment and behavior had been described. What was completely missing, though, was an understanding of the neural activity underlying the formation of the memory. The behaviorists had deliberately shied away from physiological explanations because of the intangible nature of neural activity at that time.Then the climate began to change. Karl Lashley had shown that lesions in the cerebral cortex had predictable effects on behavior in animals (Lashley 1929, 1950), and Donald Hebb introduced concepts and ideas to account for complex brain functions at the neural circuit level, many of which have retained a place in modern neuroscience (Hebb 1949). Both Lashley and Hebb searched for the engram, but they found no specific locus for it. A significant turning point was reached when Scoville and Milner (1957) reported severe loss of memory in an epileptic patient, patient H.M., after bilateral surgical removal of the hippocampal formation and the surrounding medial temporal lobe areas. “After operation this young man could no longer recognize the hospital staff nor find his way to the bathroom, and he seemed to recall nothing of the day-to-day events of his hospital life.” This tragic misfortune inspired decades of research on the function of the hippocampus in memory. H.M.’s memory impairment could be reproduced in memory tasks in animals and studies of H.M., as well as laboratory animals, pointed to a critical role for the hippocampus in declarative memory—memory, which, in humans, can be consciously recalled and declared, such as memories of experiences and facts (Milner et al. 1968; Mishkin 1978; Cohen and Squire 1980; Squire 1992; Corkin 2002). What was missing from these early studies, however, was a way to address the neuronal mechanisms that led information to be stored as memory.The aim of this article is to show how studies of hippocampal neuronal activity during the past few decades have brought us to a point at which a mechanistic basis of memory formation is beginning to surface. An early landmark in this series of investigations was the discovery of place cells, cells that fire selectively at one or few locations in the environment. At first, these cells seemed to be part of the animal’s instantaneous representation of location, independent of memory, but gradually, over the course of several decades, it has become clear that place cells express current as well as past and future locations. In many ways, place cells can be used as readouts of the memories that are stored in the hippocampus. More recent work has also shown that place cells are part of a wider network of spatially modulated neurons, including grid, border, and head direction cells, each with distinct roles in the representation of space and spatial memory. In this article, we shall discuss potential mechanisms by which these cell types, particularly place and grid cells, in conjunction with synaptic plasticity, may form the basis of a mammalian system for fast high-capacity declarative memory.     

Synaptic Scaling Enables Dynamically Distinct Short- and Long-Term Memory Formation

Memory storage in the brain relies on mechanisms acting on time scales from minutes, for long-term synaptic potentiation, to days, for memory consolidation. During such processes, neural circuits distinguish synapses relevant for forming a long-term storage, which are consolidated, from synapses of short-term storage, which fade. How time scale integration and synaptic differentiation is simultaneously achieved remains unclear. Here we show that synaptic scaling – a slow process usually associated with the maintenance of activity homeostasis – combined with synaptic plasticity may simultaneously achieve both, thereby providing a natural separation of short- from long-term storage. The interaction between plasticity and scaling provides also an explanation for an established paradox where memory consolidation critically depends on the exact order of learning and recall. These results indicate that scaling may be fundamental for stabilizing memories, providing a dynamic link between early and late memory formation processes.     

The Phosphodiesterase 9 Inhibitor PF‐04449613 Promotes Dendritic Spine Formation and Performance Improvement after Motor Learning

The cyclic nucleotide cGMP is an intracellular second messenger with important roles in neuronal functions and animals' behaviors. The phosphodiesterases (PDEs) are a family of enzymes that hydrolyze the second messengers cGMP and cAMP. Inhibition of phosphodiesterase 9 (PDE9), a main isoform of PDEs hydrolyzing cGMP, has been shown to improve learning and memory as well as cognitive function in rodents. However, the role of PDE9 in regulating neuronal structure and function in vivo remains unclear. Here we used in vivo two‐photon microscopy to investigate the effect of a selective PDE9 inhibitor PF‐04449613 on the activity and plasticity of dendritic spines of layer V pyramidal neurons in the mouse primary motor cortex. We found that administration of PF‐04449613 increased calcium activity of dendrites and dendritic spines of layer V pyramidal neurons in mice under resting and running conditions. Chronic treatment of PF‐04449613 over weeks increased dendritic spine formation and elimination under basal conditions. Furthermore, PF‐04449613 treatment over 1–7 days increased the formation and survival of new spines as well as performance improvement after rotarod motor training. Taken together, our studies suggest that elevating the level of cGMP with the PDE9 inhibitor PF‐04449613 increases synaptic calcium activity and learning‐dependent synaptic plasticity, thereby contributing to performance improvement after learning. © 2018 Wiley Periodicals, Inc. Develop Neurobiol 00: 000–000, 2018     

Human dorsal and ventral auditory streams subserve rehearsal-based and echoic processes during verbal working memory

To hear a sequence of words and repeat them requires sensory-motor processing and something more-temporary storage. We investigated neural mechanisms of verbal memory by using fMRI and a task designed to tease apart perceptually based ("echoic") memory from phonological-articulatory memory. Sets of two- or three-word pairs were presented bimodally, followed by a cue indicating from which modality (auditory or visual) items were to be retrieved and rehearsed over a delay. Although delay-period activation in the planum temporale (PT) was insensible to the source modality and showed sustained delay-period activity, the superior temporal gyrus (STG) activated more vigorously when the retrieved items had arrived to the auditory modality and showed transient delay-period activity. Functional connectivity analysis revealed two topographically distinct fronto-temporal circuits, with STG co-activating more strongly with ventrolateral prefrontal cortex and PT co-activating more strongly with dorsolateral prefrontal cortex. These argue for separate contributions of ventral and dorsal auditory streams in verbal working memory.     

Drosophila fasciclinII is required for the formation of odor memories and for normal sensitivity to alcohol.

Drosophila fasciclinII (fasII) mutants perform poorly after olfactory conditioning due to a defect in encoding, stabilizing, or retrieving short-term memories. Performance was rescued by inducing the expression of a normal transgene just before training and immediate testing. Induction after training but before testing failed to rescue performance, showing that Fas II does not have an exclusive role in memory retrieval processes. The stability of odor memories in fasII mutants are indistinguishable from control animals when initial performance is normalized. Like several other mutants deficient in odor learning, fasII mutants exhibit a heightened sensitivity to ethanol vapors. A combination of behavioral and genetic strategies have therefore revealed a role for Fas II in the molecular operations of encoding short-term odor memories and conferring alcohol sensitivity. The preferential expression of Fas II in the axons of mushroom body neurons furthermore suggests that short-term odor memories are formed in these neurites.     

A model of late long-term potentiation simulates aspects of memory maintenance

Late long-term potentiation (L-LTP) denotes long-lasting strengthening of synapses between neurons. L-LTP appears essential for the formation of long-term memory, with memories at least partly encoded by patterns of strengthened synapses. How memories are preserved for months or years, despite molecular turnover, is not well understood. Ongoing recurrent neuronal activity, during memory recall or during sleep, has been hypothesized to preferentially potentiate strong synapses, preserving memories. This hypothesis has not been evaluated in the context of a mathematical model representing ongoing activity and biochemical pathways important for L-LTP. In this study, ongoing activity was incorporated into two such models - a reduced model that represents some of the essential biochemical processes, and a more detailed published model. The reduced model represents synaptic tagging and gene induction simply and intuitively, and the detailed model adds activation of essential kinases by Ca(2+). Ongoing activity was modeled as continual brief elevations of Ca(2+). In each model, two stable states of synaptic strength/weight resulted. Positive feedback between synaptic weight and the amplitude of ongoing Ca(2+) transients underlies this bistability. A tetanic or theta-burst stimulus switches a model synapse from a low basal weight to a high weight that is stabilized by ongoing activity. Bistability was robust to parameter variations in both models. Simulations illustrated that prolonged periods of decreased activity reset synaptic strengths to low values, suggesting a plausible forgetting mechanism. However, episodic activity with shorter inactive intervals maintained strong synapses. Both models support experimental predictions. Tests of these predictions are expected to further understanding of how neuronal activity is coupled to maintenance of synaptic strength. Further investigations that examine the dynamics of activity and synaptic maintenance can be expected to help in understanding how memories are preserved for up to a lifetime in animals including humans.