scholarly journals Quantitative investigation of memory recall performance of a computational microcircuit model of the hippocampus

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Nikolaos Andreakos ◽  
Shigang Yue ◽  
Vassilis Cutsuridis
Keyword(s):  
Recall Performance ◽  
Network Size ◽  
Excitatory Input ◽  
Quantitative Investigation ◽  
Great Cost ◽  
Neuronal Populations ◽  
Global Threshold ◽  
Tightly Coupled ◽  
Memory Pattern ◽  
Determining Factor

AbstractMemory, the process of encoding, storing, and maintaining information over time to influence future actions, is very important in our lives. Losing it, it comes with a great cost. Deciphering the biophysical mechanisms leading to recall improvement should thus be of outmost importance. In this study, we embarked on the quest to improve computationally the recall performance of a bio-inspired microcircuit model of the mammalian hippocampus, a brain region responsible for the storage and recall of short-term declarative memories. The model consisted of excitatory and inhibitory cells. The cell properties followed closely what is currently known from the experimental neurosciences. Cells’ firing was timed to a theta oscillation paced by two distinct neuronal populations exhibiting highly regular bursting activity, one tightly coupled to the trough and the other to the peak of theta. An excitatory input provided to excitatory cells context and timing information for retrieval of previously stored memory patterns. Inhibition to excitatory cells acted as a non-specific global threshold machine that removed spurious activity during recall. To systematically evaluate the model’s recall performance against stored patterns, pattern overlap, network size, and active cells per pattern, we selectively modulated feedforward and feedback excitatory and inhibitory pathways targeting specific excitatory and inhibitory cells. Of the different model variations (modulated pathways) tested, ‘model 1’ recall quality was excellent across all conditions. ‘Model 2’ recall was the worst. The number of ‘active cells’ representing a memory pattern was the determining factor in improving the model’s recall performance regardless of the number of stored patterns and overlap between them. As ‘active cells per pattern’ decreased, the model’s memory capacity increased, interference effects between stored patterns decreased, and recall quality improved.

scholarly journals Quantitative Investigation Of Memory Recall Performance Of A Computational Microcircuit Model Of The Hippocampus

2020 ◽  
Author(s):  
Nikolaos Andreakos ◽  
Shigang Yue ◽  
Vassilis Cutsuridis
Keyword(s):  
Recall Performance ◽  
Network Size ◽  
Excitatory Input ◽  
Quantitative Investigation ◽  
Great Cost ◽  
Neuronal Populations ◽  
Global Threshold ◽  
Tightly Coupled ◽  
Memory Pattern ◽  
Determining Factor

Abstract Memory, the process of encoding, storing, and maintaining information over time in order to influence future actions, is very important in our lives. Losing it, it comes with a great cost. Deciphering the biophysical mechanisms leading to recall improvement should thus be of outmost importance. In this study we embarked on the quest to improve computationally the recall performance of a bio-inspired microcircuit model of the mammalian hippocampus, a brain region responsible for the storage and recall of short-term declarative memories. The model consisted of excitatory and inhibitory cells. The cell properties followed closely what is currently known from the experimental neurosciences. Cells’ firing was timed to a theta oscillation paced by two distinct neuronal populations exhibiting highly regular bursting activity, one tightly coupled to the trough and the other to the peak of theta. An excitatory input provided to excitatory cells context and timing information for retrieval of previously stored memory patterns. Inhibition to excitatory cells acted as a non-specific global threshold machine that removed spurious activity during recall. To systematically evaluate the model’s recall performance against stored patterns, pattern overlap, network size and active cells per pattern, we selectively modulated feedforward and feedback excitatory and inhibitory pathways targeting specific excitatory and inhibitory cells. Of the different model variations (modulated pathways) tested, ‘model 1’ recall quality was excellent across all conditions. ‘Model 2’ recall was the worst. The number of ‘active cells’ representing a memory pattern was the determining factor in improving the model’s recall performance regardless of the number of stored patterns and overlap between them. As ‘active cells per pattern’ decreased, the model’s memory capacity increased, interference effects between stored patterns decreased, and recall quality improved.

Why Do High-Status People Have Larger Social Networks? Belief in Status-Quality Coupling as a Driver of Network-Broadening Behavior and Social Network Size

2020 ◽  
Author(s):  
Jiyin Cao ◽  
Edward Bishop Smith
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Status ◽  
Positive Association ◽  
Network Size ◽  
High Status ◽  
Discussion Section ◽  
Social Network Size ◽  
Tightly Coupled ◽  
The Relationship

Previous research has demonstrated that the size and reach of people’s social networks tend to be positively related to their social status. Although several explanations help to account for this relationship—for example, higher-status people may be part of multiple social circles and therefore have more social contacts with whom to affiliate—we present a novel argument involving people’s beliefs about the relationship between status and quality, what we call status-quality coupling. Across seven separate studies, we demonstrate that the positive association between social status and network-broadening behavior (as well as social network size) is contingent on the extent to which people believe that status is a reliable indicator of quality. Across each of our studies, high- and low-status people who viewed status and quality as tightly coupled differed in their network-broadening behaviors, as well as in the size of their reported social networks. The effect was largely driven by the perceived self-value and perceived receptivity of the networking target. Such differences were significantly weaker or nonexistent among equivalently high- and low-status people who viewed status as an unreliable indicator of quality. Because the majority of participants—both high- and low-status—exhibited beliefs in status-quality coupling, we conclude that such a belief marks an important and previously unaccounted-for driver of the relationship between status, network-broadening behaviors, and social networks. Implications for research on social capital, advice seeking, and inequality are highlighted in the discussion section.

scholarly journals Neural gain control measured through cortical gamma oscillations is associated with individual variations in sensory sensitivity

2018 ◽  
Author(s):  
EV Orekhova ◽  
TA Stroganova ◽  
JF Schneiderman ◽  
S Lundström ◽  
B Riaz ◽  
...  
Keyword(s):  
Gain Control ◽  
Gamma Oscillations ◽  
Excitatory Input ◽  
Sensory Sensitivity ◽  
Motion Velocity ◽  
Neuronal Populations ◽  
Individual Variations ◽  
Two Samples ◽  
Neural Gain ◽  
Excitatory Drive

AbstractGamma oscillations facilitate information processing by shaping the excitatory input/output of neuronal populations, and their suppression by strong excitatory drive may stem from inhibitory-based gain control of network excitation. Individual variations in the gamma suppression may therefore reflect efficiency of gain control and subjective sensitivity to everyday sensory events. To test this prediction, we assessed the link between self-reported sensory sensitivity and changes in magneto-encephalographic gamma oscillations as a function of motion velocity of high-contrast visual gratings. The induced gamma oscillations increased in frequency and decreased in power with increasing stimulation intensity. As expected, weaker suppression of the gamma response correlated with sensory hypersensitivity. Robustness of this result was confirmed by its replication in the two samples: neurotypical subjects and people with autism, who had generally higher sensory sensitivity. We conclude that intensity-related suppression of gamma response is a promising biomarker of homeostatic control of the excitation-inhibition balance in the visual cortex.

scholarly journals Extracting temporal relationships between weakly coupled peptidergic and motoneuronal signaling: application to Drosophila ecdysis behavior

2021 ◽  
Author(s):  
Miguel Piñeiro ◽  
Wilson Mena ◽  
John Ewer ◽  
Patricio Orio
Keyword(s):  
Motor Behavior ◽  
Ex Vivo ◽  
Motor Sequence ◽  
Neuronal Populations ◽  
Animal Physiology ◽  
Temporal Relationships ◽  
Weakly Coupled ◽  
Tightly Coupled ◽  
Central Nervous Systems ◽  
And Behavior

Neuromodulators, such as neuropeptides, can regulate and reconfigure neural circuits to alter their output, affecting in this way animal physiology and behavior. The interplay between the activity of neuronal circuits, their modulation by neuropeptides, and the resulting behavior, is still poorly understood. Here, we present a quantitative framework to study the relationships between the temporal pattern of activity of peptidergic neurons and of motoneurons during Drosophila ecdysis behavior, a highly stereotyped motor sequence that is critical for insect growth. We analyzed, in the time and frequency domains, simultaneous intracellular calcium recordings of peptidergic CCAP (crustacean cardioactive peptide) neurons and motoneurons obtained from isolated central nervous systems throughout fictive ecdysis behavior induced ex vivo by Ecdysis triggering hormone. We found that the activity of both neuronal populations is tightly coupled in a cross-frequency manner, suggesting that CCAP neurons modulate the faster oscillation of motoneurons. To explore this idea further, we used a probabilistic logistic model to show that calcium dynamics in CCAP neurons can predict the oscillation of motoneurons, both in a simple model and in a conductance-base model capable of simulating many of the observed neural dynamics features. Finally, we developed an algorithm to quantify the motor behavior observed in videos of pupal ecdysis, and compared their features to the patterns of neuronal calcium activity recorded ex vivo . We found that the motor activity of the intact animal is more regular than the motoneuronal activity recorded from the ex vivo preparations during fictive ecdysis behavior; the analysis of movement patterns also allowed us to identify a new post-ecdysis phase.

scholarly journals Extracting temporal relationships between weakly coupled peptidergic and motoneuronal signaling: Application to Drosophila ecdysis behavior

2021 ◽  
Vol 17 (12) ◽  
pp. e1008933
Author(s):  
Miguel Piñeiro ◽  
Wilson Mena ◽  
John Ewer ◽  
Patricio Orio
Keyword(s):  
Motor Behavior ◽  
Ex Vivo ◽  
Motor Sequence ◽  
Neuronal Populations ◽  
Animal Physiology ◽  
Temporal Relationships ◽  
Weakly Coupled ◽  
Tightly Coupled ◽  
Central Nervous Systems ◽  
And Behavior

Neuromodulators, such as neuropeptides, can regulate and reconfigure neural circuits to alter their output, affecting in this way animal physiology and behavior. The interplay between the activity of neuronal circuits, their modulation by neuropeptides, and the resulting behavior, is still poorly understood. Here, we present a quantitative framework to study the relationships between the temporal pattern of activity of peptidergic neurons and of motoneurons during Drosophila ecdysis behavior, a highly stereotyped motor sequence that is critical for insect growth. We analyzed, in the time and frequency domains, simultaneous intracellular calcium recordings of peptidergic CCAP (crustacean cardioactive peptide) neurons and motoneurons obtained from isolated central nervous systems throughout fictive ecdysis behavior induced ex vivo by Ecdysis triggering hormone. We found that the activity of both neuronal populations is tightly coupled in a cross-frequency manner, suggesting that CCAP neurons modulate the frequency of motoneuron firing. To explore this idea further, we used a probabilistic logistic model to show that calcium dynamics in CCAP neurons can predict the oscillation of motoneurons, both in a simple model and in a conductance-base model capable of simulating many features of the observed neural dynamics. Finally, we developed an algorithm to quantify the motor behavior observed in videos of pupal ecdysis, and compared their features to the patterns of neuronal calcium activity recorded ex vivo. We found that the motor activity of the intact animal is more regular than the motoneuronal activity recorded from ex vivo preparations during fictive ecdysis behavior; the analysis of the patterns of movement also allowed us to identify a new post-ecdysis phase.

scholarly journals Conjunctive spatial and self-motion codes are topographically organized in the GABAergic cells of the lateral septum

PLoS Biology ◽  
2021 ◽  
Vol 19 (8) ◽  
pp. e3001383
Author(s):  
Suzanne van der Veldt ◽  
Guillaume Etter ◽  
Coralie-Anne Mosser ◽  
Frédéric Manseau ◽  
Sylvain Williams
Keyword(s):  
Dorsal Hippocampus ◽  
Pyramidal Cells ◽  
Medial Septum ◽  
Excitatory Input ◽  
Lateral Septum ◽  
Neuronal Populations ◽  
Hippocampal Ca1 ◽  
Memory Network ◽  
Self Motion

The hippocampal spatial code’s relevance for downstream neuronal populations—particularly its major subcortical output the lateral septum (LS)—is still poorly understood. Here, using calcium imaging combined with unbiased analytical methods, we functionally characterized and compared the spatial tuning of LS GABAergic cells to those of dorsal CA3 and CA1 cells. We identified a significant number of LS cells that are modulated by place, speed, acceleration, and direction, as well as conjunctions of these properties, directly comparable to hippocampal CA1 and CA3 spatially modulated cells. Interestingly, Bayesian decoding of position based on LS spatial cells reflected the animal’s location as accurately as decoding using the activity of hippocampal pyramidal cells. A portion of LS cells showed stable spatial codes over the course of multiple days, potentially reflecting long-term episodic memory. The distributions of cells exhibiting these properties formed gradients along the anterior–posterior and dorsal–ventral axes of the LS, directly reflecting the topographical organization of hippocampal inputs to the LS. Finally, we show using transsynaptic tracing that LS neurons receiving CA3 and CA1 excitatory input send projections to the hypothalamus and medial septum, regions that are not targeted directly by principal cells of the dorsal hippocampus. Together, our findings demonstrate that the LS accurately and robustly represents spatial, directional as well as self-motion information and is uniquely positioned to relay this information from the hippocampus to its downstream regions, thus occupying a key position within a distributed spatial memory network.

Extraverts Have Larger Social Network Layers

2011 ◽  
Vol 32 (3) ◽  
pp. 161-169 ◽  
Author(s):  
Thomas V. Pollet ◽  
Sam G. B. Roberts ◽  
Robin I. M. Dunbar
Keyword(s):  
Social Network ◽  
Social Relationships ◽  
Outer Layer ◽  
Network Size ◽  
Emotional Intensity ◽  
Emotional Closeness ◽  
Network Layer ◽  
Network Layers ◽  
Social Network Size

Previous studies showed that extraversion influences social network size. However, it is unclear how extraversion affects the size of different layers of the network, and how extraversion relates to the emotional intensity of social relationships. We examined the relationships between extraversion, network size, and emotional closeness for 117 individuals. The results demonstrated that extraverts had larger networks at every layer (support clique, sympathy group, outer layer). The results were robust and were not attributable to potential confounds such as sex, though they were modest in size (raw correlations between extraversion and size of network layer, .20 < r < .23). However, extraverts were not emotionally closer to individuals in their network, even after controlling for network size. These results highlight the importance of considering not just social network size in relation to personality, but also the quality of relationships with network members.

Limitations to the Spacing Effect

2005 ◽  
Vol 52 (4) ◽  
pp. 257-263 ◽  
Author(s):  
Peter P. J. L. Verkoeijen ◽  
Remy M. J. P. Rikers ◽  
Henk G. Schmidt
Keyword(s):  
Free Recall ◽  
Phase Retrieval ◽  
Incidental Learning ◽  
Factor Model ◽  
Recall Performance ◽  
Spacing Effect ◽  
Word List ◽  
Intentional Learning ◽  
Study Phase ◽  
Learning Condition

Abstract. The spacing effect refers to the finding that memory for repeated items improves when the interrepetition interval increases. To explain the spacing effect in free-recall tasks, a two-factor model has been put forward that combines mechanisms of contextual variability and study-phase retrieval (e.g., Raaijmakers, 2003 ; Verkoeijen, Rikers, & Schmidt, 2004 ). An important, yet untested, implication of this model is that free recall of repetitions should follow an inverted u-shaped relationship with interrepetition spacing. To demonstrate the suggested relationship an experiment was conducted. Participants studied a word list, consisting of items repeated at different interrepetition intervals, either under incidental or under intentional learning instructions. Subsequently, participants received a free-recall test. The results revealed an inverted u-shaped relationship between free recall and interrepetition spacing in both the incidental-learning condition and the intentional-learning condition. Moreover, for intentionally learned repetitions, the maximum free-recall performance was located at a longer interrepetition interval than for incidentally learned repetitions. These findings are interpreted in terms of the two-factor model of spacing effects in free-recall tasks.

The “How” of Animacy Effects in Episodic Memory

2015 ◽  
Vol 62 (6) ◽  
pp. 371-384 ◽  
Author(s):  
Patrick Bonin ◽  
Margaux Gelin ◽  
Betty Laroche ◽  
Alain Méot ◽  
Aurélia Bugaiska
Keyword(s):  
Memory Load ◽  
Recall Performance ◽  
Memory Task ◽  
Human Memory ◽  
Recall Rate ◽  
Interactive Imagery ◽  
Ultimate Explanation ◽  
Better Than ◽  
Observation Results

Abstract. Animates are better remembered than inanimates. According to the adaptive view of human memory ( Nairne, 2010 ; Nairne & Pandeirada, 2010a , 2010b ), this observation results from the fact that animates are more important for survival than inanimates. This ultimate explanation of animacy effects has to be complemented by proximate explanations. Moreover, animacy currently represents an uncontrolled word characteristic in most cognitive research ( VanArsdall, Nairne, Pandeirada, & Cogdill, 2015 ). In four studies, we therefore investigated the “how” of animacy effects. Study 1 revealed that words denoting animates were recalled better than those referring to inanimates in an intentional memory task. Study 2 revealed that adding a concurrent memory load when processing words for the animacy dimension did not impede the animacy effect on recall rates. Study 3A was an exact replication of Study 2 and Study 3B used a higher concurrent memory load. In these two follow-up studies, animacy effects on recall performance were again not altered by a concurrent memory load. Finally, Study 4 showed that using interactive imagery to encode animate and inanimate words did not alter the recall rate of animate words but did increase the recall of inanimate words. Taken together, the findings suggest that imagery processes contribute to these effects.

Articulatory Rehearsal Is More Than Refreshing Memory Traces

2013 ◽  
Vol 60 (2) ◽  
pp. 131-139 ◽  
Author(s):  
Ryoji Nishiyama ◽  
Jun Ukita
Keyword(s):  
Free Recall ◽  
Recall Performance ◽  
Verbal Working Memory ◽  
Verbal Information ◽  
Free Recall Task ◽  
Study Item ◽  
Phonological Representations ◽  
Memory Traces ◽  
Short Period ◽  
Serial Position Curves

This study examined whether additional articulatory rehearsal induced temporary durability of phonological representations, using a 10-s delayed nonword free recall task. Three experiments demonstrated that cumulative rehearsal between the offset of the last study item and the start of the filled delay (Experiments 1 and 3) and a fixed rehearsal of the immediate item during the subsequent interstimulus interval (Experiments 2 and 3) improved free recall performance. These results suggest that an additional rehearsal helps to stabilize phonological representations for a short period. Furthermore, the analyses of serial position curves suggested that the frequency of the articulation affected the durability of the phonological representation. The significance of these findings as clues of the mechanism maintaining verbal information (i.e., verbal working memory) is discussed.

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