Multiple Approaches to the Investigation of Cell Assembly in Memory Research-Present and Future

Understanding Sensory-Motor Disorders in Autism Spectrum Disorders by Extending Hebbian Theory: Formation of a Rigid-Autonomous Phase Sequence

Autism spectrum disorder is a neuropsychiatric disorder characterized by persistent deficits in social communication and social interaction and restricted, repetitive patterns of behavior, interests, or activities. The symptoms invariably appear in early childhood and cause significant impairment in social, occupational, and other important functions. Various abnormalities in the genetic, neurological, and endocrine systems of patients with autism spectrum disorder have been reported as the etiology; however, no clear factor leading to the onset of the disease has been identified. Additionally, higher order cognitive dysfunctions, which are represented by a lack of theory of mind, sensorimotor disorders, and memory-related disorders (e.g., flashbacks), have been reported in recent years, but no theoretical framework has been proposed to explain these behavioral abnormalities. In this study, we extended Hebb's biopsychology theory to provide a theoretical framework that comprehensively explains the various behavioral abnormalities observed in autism spectrum disorder. Specifically, we propose that a wide range of symptoms in autism spectrum disorder may be caused by the formation of a rigid-autonomous phase sequence (RAPS) in the brain. Using the RAPS formation theory, we propose a biopsychological mechanism that could be a target for the treatment of autism spectrum disorders.

Context-invariant socioemotional encoding by prefrontal ensembles

The prefrontal cortex plays a key role in social interactions, anxiety-related avoidance, and flexible context- dependent behaviors, raising the question: how do prefrontal neurons represent socioemotional information across different environments? Are contextual and socioemotional representations segregated or intermixed, and does this cause socioemotional encoding to remap or generalize across environments? To address this, we imaged neuronal activity in the medial prefrontal cortex of mice engaged in social interactions or anxiety-related avoidance within different environments. Neuronal ensembles representing context and social interaction overlapped more than expected while remaining orthogonal. Anxiety-related representations similarly generalized across environments while remaining orthogonal to contextual information. This shows how prefrontal cortex multiplexes parallel information streams using the same neurons, rather than distinct subcircuits, achieving context-invariant encoding despite context-specific reorganization of population-level activity.

Emotional Memory Processing during REM Sleep with Implications for Post-Traumatic Stress Disorder

REM sleep is important for the processing of emotional memories, including fear memories. Rhythmic interactions, especially in the theta band, between the medial prefrontal cortex (mPFC) and limbic structures are thought to play an important role, but the ways in which memory processing occurs at a mechanistic and circuits level are largely unknown. To investigate how rhythmic interactions lead to fear extinction during REM sleep, we used a biophysically based model that included the infralimbic cortex (IL), a part of the mPFC with a critical role in suppressing fear memories. Theta frequency (4-12 Hz) inputs to a given cell assembly in IL, representing an emotional memory, resulted in the strengthening of connections from the IL to the amygdala and the weakening of connections from the amygdala to the IL, resulting in the suppression of the activity of fear expression cells for the associated memory. Lower frequency (4 Hz) theta inputs effected these changes over a wider range of input strengths. In contrast, inputs at other frequencies were ineffective at causing these synaptic changes and did not suppress fear memories. Under post-traumatic stress disorder (PTSD) REM sleep conditions, rhythmic activity dissipated, and 4 Hz theta inputs to IL were ineffective, but higher-frequency (10 Hz) theta inputs to IL induced changes similar to those seen with 4 Hz inputs under normal REM sleep conditions, resulting in the suppression of fear expression cells. These results suggest why PTSD patients may repeatedly experience the same emotionally charged dreams and suggest potential neuromodulatory therapies for the amelioration of PTSD symptoms.SIGNIFICANCE STATEMENT Rhythmic interactions in the theta band between the mPFC and limbic structures are thought to play an important role in processing emotional memories, including fear memories, during REM sleep. The infralimbic cortex (IL) in the mPFC is thought to play a critical role in suppressing fear memories. We show that theta inputs to the IL, unlike other frequency inputs, are effective in producing synaptic changes that suppress the activity of fear expression cells associated with a given memory. Under PTSD REM sleep conditions, lower-frequency (4 Hz) theta inputs to the IL do not suppress the activity of fear expression cells associated with the given memory but, surprisingly, 10 Hz inputs do. These results suggest potential neuromodulatory therapies for PTSD.

The Hebb Synapse Before Hebb: Theories of Synaptic Function in Learning and Memory Before , With a Discussion of the Long-Lost Synaptic Theory of William McDougall

Since the work of Semon was rediscovered by Schacter in 1978, there has been a renewed interest is searching for the "engram" as the locus of memory in the brain and Hebb's cell assembly has been equated with Semon's engram. There have been many theories of memory involving some concept of synaptic change, culminating in the "Hebb Synapse" theory in 1949. However, Hebb said that the idea that any two cells or systems of cells that are repeatedly active at the same time will tend to become "associated," was not his idea, but an old one. In this manuscript we give an overview of some of the theories of the neural basis of learning and memory before Hebb and describe the synaptic theory of William McDougall, which appears to have been an idea ahead of its time; so far ahead of its time that it was completely ignored by his contemporaries. We conclude by examining some critiques of McDougall's theory of inhibition and with a short discussion on the fate of neuroscientists whose ideas were neglected when first presented but were accepted as important many decades later.

Over-representation of fundamental decision variables in the prefrontal cortex underlies decision bias

The brain is organized into anatomically distinct structures consisting of a variety of projection neurons. While such evolutionarily conserved neural circuit organization underlies the innate ability of animals to swiftly adapt to environments, they can cause biased cognition and behavior. Although recent studies have begun to address the causal importance of projection-neuron types as distinct computational units, it remains unclear how projection types are functionally organized in encoding variables during cognitive tasks. This review focuses on the neural computation of decision making in the prefrontal cortex and discusses what decision variables are encoded by single neurons, neuronal populations, and projection type, alongside how specific projection types constrain decision making. We focus particularly on "over-representations" of distinct decision variables in the prefrontal cortex that reflect the biological and subjective significance of the variables for the decision makers. We suggest that task-specific over-representation in the prefrontal cortex involves the refinement of the given decision making, while generalized over-representation of fundamental decision variables is associated with suboptimal decision biases, including pathological ones such as those in patients with psychiatric disorders. Such over-representation of the fundamental decision variables in the prefrontal cortex appear to be tightly constrained by afferent and efferent connections that can be optogenetically intervened on. These ideas may provide critical insights into potential therapeutic targets for psychiatric disorders, including addiction and depression.

Dynamic patterns of correlated activity in the prefrontal cortex encode information about social behavior

New technologies make it possible to measure activity from many neurons simultaneously. One approach is to analyze simultaneously recorded neurons individually, then group together neurons which increase their activity during similar behaviors into an "ensemble." However, this notion of an ensemble ignores the ability of neurons to act collectively and encode and transmit information in ways that are not reflected by their individual activity levels. We used microendoscopic GCaMP imaging to measure prefrontal activity while mice were either alone or engaged in social interaction. We developed an approach that combines a neural network classifier and surrogate (shuffled) datasets to characterize how neurons synergistically transmit information about social behavior. Notably, unlike optimal linear classifiers, a neural network classifier with a single linear hidden layer can discriminate network states which differ solely in patterns of coactivity, and not in the activity levels of individual neurons. Using this approach, we found that surrogate datasets which preserve behaviorally specific patterns of coactivity (correlations) outperform those which preserve behaviorally driven changes in activity levels but not correlated activity. Thus, social behavior elicits increases in correlated activity that are not explained simply by the activity levels of the underlying neurons, and prefrontal neurons act collectively to transmit information about socialization via these correlations. Notably, this ability of correlated activity to enhance the information transmitted by neuronal ensembles is diminished in mice lacking the autism-associated gene Shank3. These results show that synergy is an important concept for the coding of social behavior which can be disrupted in disease states, reveal a specific mechanism underlying this synergy (social behavior increases correlated activity within specific ensembles), and outline methods for studying how neurons within an ensemble can work together to encode information.

Donald O. Hebb and the Organization of Behavior: 17 years in the writing

The Organization of Behavior has played a significant part in the development of behavioural neuroscience for the last 70 years. This book introduced the concepts of the "Hebb synapse", the "Hebbian cell assembly" and the "Phase sequence". The most frequently cited of these is the Hebb synapse, but the cell assembly may be Hebb's most important contribution. Even after 70 years, Hebb's theory is still relevant because it is a general framework for relating behavior to synaptic organization through the development of neural networks. The Organization of Behavior was Hebb's 40th publication. His first published papers in 1937 were on the innate organization of the visual system and he first used the phrase "the organization of behavior" in 1938. However, Hebb wrote a number of unpublished papers between 1932 and 1945 in which he developed the ideas published in The Organization of Behavior. Thus, the concept of the neural organization of behavior was central to Hebb's thinking from the beginning of his academic career. But his thinking about the organization of behavior in 1949 was different from what it was between 1932 and 1937. This paper examines Hebb's early ideas on the neural basis of behavior and attempts to trace the rather arduous series of steps through which he developed these ideas into the book that was published as The Organization of Behavior. Using the 1946 typescript and Hebb's correspondence we can see a number of changes made in the book before it was published. Finally, a number of issues arising from the book, and the importance of the book today are discussed.

Dynamics of memory engrams

In this update article, we focus on "memory engrams", which are traces of long-term memory in the brain, and emphasizes that they are not static but dynamic. We first introduce the major findings in neuroscience and psychology reporting that memory engrams are sometimes diffuse and unstable, indicating that they are dynamically modified processes of consolidation and reconsolidation. Second, we introduce and discuss the concepts of cell assembly and engram cell, the former has been investigated by psychological experiments and behavioral electrophysiology and the latter is defined by recent combination of activity-dependent cell labelling with optogenetics to show causal relationships between cell population activity and behavioral changes. Third, we discuss the similarities and differences between the cell assembly and engram cell concepts to reveal the dynamics of memory engrams. We also discuss the advantages and problems of live-cell imaging, which has recently been developed to visualize multineuronal activities. The last section suggests the experimental strategy and background assumptions for future research of memory engrams. The former encourages recording of cell assemblies from different brain regions during memory consolidation-reconsolidation processes, while the latter emphasizes the multipotentiality of neurons and regions that contribute to dynamics of memory engrams in the working brain.

Temporal Flexibility of Systems Consolidation and the Synaptic Occupancy/Reset Theory (SORT): Cues About the Nature of the Engram

The ability to adapt to new situations involves behavioral changes expressed either from an innate repertoire, or by acquiring experience through memory consolidation mechanisms, by far a much richer and flexible source of adaptation. Memory formation consists of two interrelated processes that take place at different spatial and temporal scales, Synaptic Consolidation, local plastic changes in the recruited neurons, and Systems Consolidation, a process of gradual reorganization of the explicit/declarative memory trace between hippocampus and the neocortex. In this review, we summarize some converging experimental results from our lab that support a normal temporal framework of memory systems consolidation as measured both from the anatomical and the psychological points of view, and propose a hypothetical model that explains these findings while predicting other phenomena. Then, the same experimental design was repeated interposing additional tasks between the training and the remote test to verify for any interference: we found that (a) when the animals were subject to a succession of new learnings, systems consolidation was accelerated, with the disengagement of the hippocampus taking place before the natural time point of this functional switch, but (b) when a few reactivation sessions reexposed the animal to the training context without the shock, systems consolidation was delayed, with the hippocampus prolonging its involvement in retrieval. We hypothesize that new learning recruits from a fixed number of plastic synapses in the CA1 area to store the engram index, while reconsolidation lead to a different outcome, in which additional synapses are made available. The first situation implies the need of a reset mechanism in order to free synapses needed for further learning, and explains the acceleration observed under intense learning activity, while the delay might be explained by a different process, able to generate extra free synapses: depending on the cognitive demands, it deals either with a fixed or a variable pool of available synapses. The Synaptic Occupancy/Reset Theory (SORT) emerged as an explanation for the temporal flexibility of systems consolidation, to encompass the two different dynamics of explicit memories, as well as to bridge both synaptic and systems consolidation in one single mechanism.