Assembly Hypothesis Research Articles

Neural Synchrony and Network Dynamics in Social Interaction: A Hyper-Brain Cell Assembly Hypothesis.

Mounting neurophysiological evidence suggests that interpersonal interaction relies on continual communication between cell assemblies within interacting brains and continual adjustments of these neuronal dynamic states between the brains. In this Hypothesis and Theory article, a Hyper-Brain Cell Assembly Hypothesis is suggested on the basis of a conceptual review of neural synchrony and network dynamics and their roles in emerging cell assemblies within the interacting brains. The proposed hypothesis states that such cell assemblies can emerge not only within, but also between the interacting brains. More precisely, the hyper-brain cell assembly encompasses and integrates oscillatory activity within and between brains, and represents a common hyper-brain unit, which has a certain relation to social behavior and interaction. Hyper-brain modules or communities, comprising nodes across two or several brains, are considered as one of the possible representations of the hypothesized hyper-brain cell assemblies, which can also have a multidimensional or multilayer structure. It is concluded that the neuronal dynamics during interpersonal interaction is brain-wide, i.e., it is based on common neuronal activity of several brains or, more generally, of the coupled physiological systems including brains.

Sensory Chunking and the Like: Testing a Pedagogical Treatment Applied to the Strengthening of the Third-Person Singular-s

Research into foreign language acquisition reports that learners of English as a foreign language are inconsistent with the suppliance of verbal morphology and tend to omit morphemes such as the third-person singular -s even at advanced instructional stages. Researchers rely on Generative linguistics and models such as the Minimalist Programme (Chomsky, 2000, 2015/1995) and the Feature Assembly Hypothesis (Lardiere, 2005, 2007, 2009) to account for such variability. The present study attempted to increase the accuracy rates of the -s. The author designed a treatment (©2018, 2019, Verónica Mendoza Fernández) that centered around sensory chunking (teaching with chunked sentences). Sixty-four learners of English as a foreign language from three different rural schools of primary education in Northern Spain participated in a classroom experiment that followed a pretest-postest procedure. Participants from school 1 constituted the control group and participants from schools 2 and 3, the experimental groups. The results of a grammaticality judgement task indicated a statistically significant increase in the accuracy rates of the -s for one of the experimental groups and a trend towards significance for the other experimental group. The treatment could promote the learning of linguistic items contained within blocks of language, as well as the learning of such blocks, and thus foster language automatisation.

A Protein Assembly Hypothesis for Population-Specific Decrease in Dementia with Time

A recent report in the journal, Neurology, documents age-normalized, nation-specific (e.g., United States and Western Europe), progressive decrease of dementia, beginning about 25 years ago. This observation has, thus far, not had explanation. We begin our proposed explanation with the following previous disease construct. (1) Some dementia is caused by innate immune over-response to infections. (2) The innate immune over-response occurs via excessive conversion of amyloid protein to α-sheet conformation. (3) This conversion evolved to inhibit invading microbes by binding microbe-associated α-sheet, e.g., in hyper-expanded capsid intermediates of some viruses. The rarity of human α-sheet makes this inhibition specific for microbial invaders. As foundation, here we observe directly, for the first time, extreme, sheet-like outer shell thinness in a hyper-expanded capsid of phage T3. Based on phage/herpesvirus homology, we propose the following. The above decrease in dementia is caused by varicella-zoster virus (VZV) vaccination, USFDA-approved about 25 years ago; VZV is a herpesvirus and causes chickenpox and shingles. In China and Japan, a cotemporaneous non-decrease is explained by lower anti-VZV vaccination. Co-assembly extension of α-sheet is relatively independent of amino acid sequence. Thus, we project that additional dementia is suppressible by vaccination against other viruses, including other herpesviruses.

Neuronal Assemblies Evidence Distributed Interactions within a Tactile Discrimination Task in Rats.

Accumulating evidence suggests that neural interactions are distributed and relate to animal behavior, but many open questions remain. The neural assembly hypothesis, formulated by Hebb, states that synchronously active single neurons may transiently organize into functional neural circuits—neuronal assemblies (NAs)—and that would constitute the fundamental unit of information processing in the brain. However, the formation, vanishing, and temporal evolution of NAs are not fully understood. In particular, characterizing NAs in multiple brain regions over the course of behavioral tasks is relevant to assess the highly distributed nature of brain processing. In the context of NA characterization, active tactile discrimination tasks with rats are elucidative because they engage several cortical areas in the processing of information that are otherwise masked in passive or anesthetized scenarios. In this work, we investigate the dynamic formation of NAs within and among four different cortical regions in long-range fronto-parieto-occipital networks (primary somatosensory, primary visual, prefrontal, and posterior parietal cortices), simultaneously recorded from seven rats engaged in an active tactile discrimination task. Our results first confirm that task-related neuronal firing rate dynamics in all four regions is significantly modulated. Notably, a support vector machine decoder reveals that neural populations contain more information about the tactile stimulus than the majority of single neurons alone. Then, over the course of the task, we identify the emergence and vanishing of NAs whose participating neurons are shown to contain more information about animal behavior than randomly chosen neurons. Taken together, our results further support the role of multiple and distributed neurons as the functional unit of information processing in the brain (NA hypothesis) and their link to active animal behavior.

The One-Sample PARAFAC Approach Reveals Molecular Size Distributions of Fluorescent Components in Dissolved Organic Matter.

Molecular size plays an important role in dissolved organic matter (DOM) biogeochemistry, but its relationship with the fluorescent fraction of DOM (FDOM) remains poorly resolved. Here high-performance size exclusion chromatography (HPSEC) was coupled to fluorescence emission-excitation (EEM) spectroscopy in full spectral (60 emission and 34 excitation wavelengths) and chromatographic resolution (<1 Hz), to enable the mathematical decomposition of fluorescence on an individual sample basis by parallel factor analysis (PARAFAC). The approach allowed cross-system comparisons of molecular size distributions for individual fluorescence components obtained from independent data sets. Spectra extracted from allochthonous DOM were highly similar. Allochthonous and autochthonous DOM shared some spectra, but included unique components. In agreement with the supramolecular assembly hypothesis, molecular size distributions of the fluorescence fractions were broad and chromatographically unresolved, possibly representing reoccurring fluorophores forming noncovalently bound assemblies of varying molecular size. Samples shared underlying fluorescence components that differed in their size distributions but not their spectral properties. Thus, in contrast to absorption measurements, bulk fluorescence is unlikely to reliably indicate the average molecular size of DOM. The one-sample approach enables robust and independent cross-site comparisons without large-scale sampling efforts and introduces new analytical opportunities for elucidating the origins and biogeochemical properties of FDOM.

Unraveling the size‐dependent optical properties of dissolved organic matter

AbstractThe size‐dependent optical properties of dissolved organic matter (DOM) from four Swedish lakes were investigated using High Performance Size Exclusion Chromatography (HPSEC) in conjunction with online characterization of absorbance (240–600 nm) and fluorescence (excitation: 275 nm, emission: 300–600 nm). The molecular size of chromophoric DOM (CDOM) was consistently higher than that of fluorescent DOM (FDOM), with an average difference of 0.37 kDa. The relative abundance of FDOM vs. CDOM ranged from 0.3 to 0.7 across lakes, and increased with decreasing average molecular size. Across sites, the CDOM spectral slopes of the large molecular size fraction were highly similar while the low molecular size fraction differed and contributed to different bulk spectral slopes. Our results indicate structural congruence of high molecular size DOM across systems while lake trophic status determined the characteristics of the low size range. Furthermore, the combination of HPSEC and parallel factor analysis (HPSEC‐PARAFAC2) allowed the decomposition of DOM fluorescence chromatograms. Three humic‐like components and one protein‐like component with broadly overlapping molecular size distributions were identified. This overlap provides further evidence for the supramolecular assembly hypothesis since fluorophores, as revealed by PARAFAC2, occur in aggregates of overlapping molecular size. Our results further suggest a link between the molecular size of these fluorophores and the associated supramolecular assemblies. This study demonstrates the potential for HPSEC and novel mathematical approaches to provide unprecedented insights into the relationship between optical and chemical properties of DOM in aquatic systems.

Interaction between memories in an abstract mathematical model based on the Hebbian cell assembly hypothesis

Learning and memory are essential properties of adaptive neural circuits. Thereby, the general hypothesis (Synaptic-Plasticity-and-Memory hypothesis; [1,2]) is that the adaptive process of synaptic plasticity induces changes at the synapses connecting the neurons. These changes lead to the formation of strongly interconnected subgroups of neurons, so-called cell assemblies [3]. It has been suggested that such cell assemblies represent the learned memory items. However, as known from everyday life, after learning, humans and animals show the remarkable ability to connect, generalize, and discriminate old and new memories. How these memory interactions are realized on a neuronal level based on the idea of cell assemblies is still unknown. In this work, we use a network model dependent on the interaction between synaptic plasticity and synaptic scaling [4,5]. Amongst others, this interaction yields the formation of cell assemblies showing dynamics comparable to human memories [6]. For simplicity, here, we further abstract this complex network model by the methods of mean-field theory. Thereby, the dynamics of each cell assembly in the network are reduced to two differential equations; one for the average neuronal activity and one for the average synaptic weight. Given this simplified model, we show that, in contrast to loosely connected groups of neurons, the formation of cell assemblies lets the activity of the neuronal population follow a hysteresis which creates complex network dynamics, which depend on the initial conditions. Given this hysteresis, in the next step, we connect two such assemblies with each other by plastic connections also adapted by the interaction between synaptic plasticity and scaling. Amongst others, we analyzed under which circumstances the dynamics of this two-cell-assembly system are comparable to the above mentioned dynamics of human and animal memories and how different parameters of the system (e.g., cell assembly size) influence them. In summary, this work is one of the first using a mathematical model to relate the dynamics of memories on a psychological scale to the hypothesized dynamics of cell assemblies on a neuronal scale.

Cell Assembly Signatures Defined by Short-Term Synaptic Plasticity in Cortical Networks.

The cell assembly (CA) hypothesis has been used as a conceptual framework to explain how groups of neurons form memories. CAs are defined as neuronal pools with synchronous, recurrent and sequential activity patterns. However, neuronal interactions and synaptic properties that define CAs signatures have been difficult to examine because identities and locations of assembly members are usually unknown. In order to study synaptic properties that define CAs, we used optical and electrophysiological approaches to record activity of identified neurons in mouse cortical cultures. Population analysis and graph theory techniques allowed us to find sequential patterns that represent repetitive transitions between network states. Whole cell pair recordings of neurons participating in repeated sequences demonstrated that synchrony is exhibited by groups of neurons with strong synaptic connectivity (concomitant firing) showing short-term synaptic depression (STD), whereas alternation (sequential firing) is seen in groups of neurons with weaker synaptic connections showing short-term synaptic facilitation (STF). Decreasing synaptic weights of a network promoted the generation of sequential activity patterns, whereas increasing synaptic weights restricted state transitions. Thus in simple cortical networks of real neurons, basic signatures of CAs, the properties that underlie perception and memory in Hebb's original description, are already present.

Abstract 1894: Extensive genomic profiling of a rare extranodal-follicular dendritic cell sarcoma: Implications for future individualized therapy

Abstract Background: Extranodal follicular dendritic cell sarcoma (FDCS) is an exceedingly rare tumor type that is limited to few cases in the literature. Given the rarity of this tumor, there is a lack of genetic understanding of this disease resulting in a non-individualized plan of care for patients with this disease. Herein, we are the first to describe extensively molecularly the DNA and RNA of this tumor. Methods: Under an IRB approved protocol, the patient's tumor and whole blood was freshly frozen for molecular analysis. We performed Next Generation Sequencing (NGS) genomic profiling including exome capture, mate pair and mRNA sequencing on this tumor. Exome and mRNA data were processed through Mayo's Bioinformatics Core standard pipelines, GENOME GPS 1.2.1 and MAPRSeq v1.2.1. Mutations and indels were prioritized depending on whether or not they belonged to known cancer associated genes. Copy number variations (CNVs) in Exome and Mate Pair data was found through PatternCNV v 1.0.1 and fusion transcripts were found using SNOWSHOES-FTD and Tophat-Fusion 2.0.6. Results: At the genomic level large scale genomic rearrangements were detected, including chr19 and chr20 trisomy, chr15q and chr17q segmental duplications result in two intra-chromosomal fusion genes, and translocations leading to four inter-chromosomal fusion genes between chr15 and chr17. Of particular interest is a stop codon gain in the CLTC1 (chr22) gene, which is involved in the mitotic spindle organization which has been associated with meningiomas and breast tumorigenesis. The new stop codon is before the site required for the recruitment of the proteins to the spindle. The large scale genomic rearrangement described above is consistent with this defective spindle assembly hypothesis. Another intriguing mutation detected in the VEGFR1 (chr13) gene leads to a 45% mis-spliced transcript. VEGFR1 is thought to modulate VEGFR2 which plays an essential role in angiogenesis, by acting as a decoy receptor. Therefore the loss of function of VEGFR1 might lead to hyper-activity of VEGFR2 pathway and a potential therapeutic strategy is to directly inhibit the VEGFR2 pathway. Furthermore missense mutations in the ATM (chr11) and TP53 (chr17) genes were found. PARP inhibitors have been used with success for cancer with defects in the ATM gene. Finally a novel fusion transcript of HDGRFP3 (chr15) and SHC4 (chr15) was identified. Such fusion results in an overexpressed SHC4 gene which has been associated with metastatic melanomas. Conclusions: In summary, genomic profiling of a rare thyroid FDCS identified drug targetable genes as well as changes related to tumor etiology. Future work is necessary to determine the functional significance of these molecular findings and whether they will predict benefit to targeted therapies. Citation Format: Jaime I. Davila, Jason Starr, Steven Attia, Chen Wang, Xue Wang, Brian Necela, Casler John, David Menke, Vivek Sarangi, Gavin Oliver, Richard Joseph, John Copland, Alexander Parker, E. Aubrey Thompson, Robert Smallridge, Yan W. Asmann. Extensive genomic profiling of a rare extranodal-follicular dendritic cell sarcoma: Implications for future individualized therapy. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1894. doi:10.1158/1538-7445.AM2014-1894

Structure of arginine overlayers at the aqueous gold interface: implications for nanoparticle assembly.

Adsorption of small biomolecules onto the surface of nanoparticles offers a novel route to generation of nanoparticle assemblies with predictable architectures. Previously, ligand-exchange experiments on citrate-capped gold nanoparticles with the amino acid arginine were reported to support linear nanoparticle assemblies. Here, we use a combination of atomistic modeling with experimental characterization to explore aspects of the assembly hypothesis for these systems. Using molecular simulation, we probe the structural and energetic characteristics of arginine overlayers on the Au(111) surface under aqueous conditions at both low- and high-coverage regimes. In the low-density regime, the arginines lie flat on the surface. At constant composition, these overlayers are found to be lower in energy than the densely packed films, although the latter case appears kinetically stable when arginine is adsorbed via the zwitterion group, exposing the charged guanidinium group to the solvent. Our findings suggest that zwitterion-zwitterion hydrogen bonding at the gold surface and minimization of the electrostatic repulsion between adjacent guanidinium groups play key roles in determining arginine overlayer stability at the aqueous gold interface. Ligand-exchange experiments of citrate-capped gold nanoparticles with arginine derivatives agmatine and N-methyl-l-arginine reveal that modification at the guanidinium group significantly diminishes the propensity for linear assembly of the nanoparticles.

The role of abiotic environmental conditions and herbivory in shaping bacterial community composition in floral nectar.

Identifying the processes that drive community assembly has long been a central theme in ecology. For microorganisms, a traditional prevailing hypothesis states that “everything is everywhere, but the environment selects”. Although the bacterial community in floral nectar may be affected by both atmosphere (air-borne bacteria) and animals as dispersal vectors, the environmental and geographic factors that shape microbial communities in floral nectar are unknown. We studied culturable bacterial communities in Asphodelus aestivus floral nectar and in its typical herbivorous bug Capsodes infuscatus, along an aridity gradient. Bacteria were sampled from floral nectar and bugs at four sites, spanning a geographical range of 200 km from Mediterranean to semi-arid conditions, under open and bagged flower treatments. In agreement with the niche assembly hypothesis, the differences in bacterial community compositions were explained by differences in abiotic environmental conditions. These results suggest that microbial model systems are useful for addressing macro-ecological questions. In addition, similar bacterial communities were found in the nectar and on the surface of the bugs that were documented visiting the flowers. These similarities imply that floral nectar bacteria dispersal is shaped not only by air borne bacteria and nectar consumers as previously reported, but also by visiting vectors like the mirid bugs.

Local detection of communities by an analogy to memory recall in the brain

Abstract In network science a ‘community’ refers to a group of nodes in a network that are densely connected within this group but are less connected with nodes outside this group. Community structure is a hallmark of a variety of social, biological and engineering networks, and development of effective and efficient methods for detecting communities in networks has been a central issue of network science. We put forward a method of local detection of communities inspired by the cell assembly hypothesis, which has been longstanding and prevailing in neuroscience. The hypothesis states that: Neurons coding a specific item tend to be mutually connected, thus forming a ‘cell assembly’; memory recall of the item is associated with reverberative activation of neurons comprising the cell assembly. Here we compare communities to cell assemblies and propose to detect communities in networks by use of the dynamics modeling neural mechanisms for memory recall in the brain. Community detection from benchmark networks by the proposed method is perfect or highly accurate. These results demonstrate the validity of local detection of communities that is processed in an analogy to memory recall in the brain.

Ensemble of Secondary Structures for Encapsidated Satellite Tobacco Mosaic Virus RNA Consistent with Chemical Probing and Crystallography Constraints

Viral genomic RNA adopts many conformations during its life cycle as the genome is replicated, translated, and encapsidated. The high-resolution crystallographic structure of the satellite tobacco mosaic virus (STMV) particle reveals 30 helices of well-ordered RNA. The crystallographic data provide global constraints on the possible secondary structures for the encapsidated RNA. Traditional free energy minimization methods of RNA secondary structure prediction do not generate structures consistent with the crystallographic data, and to date no complete STMV RNA basepaired secondary structure has been generated. RNA-protein interactions and tertiary interactions may contribute a significant degree of stability, and the kinetics of viral assembly may dominate the folding process. The computational tools, Helix Find & Combine, Crumple, and Sliding Windows and Assembly, evaluate and explore the possible secondary structures for encapsidated STMV RNA. All possible hairpins consistent with the experimental data and a cotranscriptional folding and assembly hypothesis were generated, and the combination of hairpins that was most consistent with experimental data is presented as the best representative structure of the ensemble. Multiple solutions to the genome packaging problem could be an evolutionary advantage for viruses. In such cases, an ensemble of structures that share favorable global features best represents the RNA fold.

Neuronal Assembly Detection and Cell Membership Specification by Principal Component Analysis

In 1949, Donald Hebb postulated that assemblies of synchronously activated neurons are the elementary units of information processing in the brain. Despite being one of the most influential theories in neuroscience, Hebb's cell assembly hypothesis only started to become testable in the past two decades due to technological advances. However, while the technology for the simultaneous recording of large neuronal populations undergoes fast development, there is still a paucity of analytical methods that can properly detect and track the activity of cell assemblies. Here we describe a principal component-based method that is able to (1) identify all cell assemblies present in the neuronal population investigated, (2) determine the number of neurons involved in ensemble activity, (3) specify the precise identity of the neurons pertaining to each cell assembly, and (4) unravel the time course of the individual activity of multiple assemblies. Application of the method to multielectrode recordings of awake and behaving rats revealed that assemblies detected in the cerebral cortex and hippocampus typically contain overlapping neurons. The results indicate that the PCA method presented here is able to properly detect, track and specify neuronal assemblies, irrespective of overlapping membership.

An evolutionarily conserved mechanism for presynaptic trapping.

Presynaptic differentiation takes place over three interrelated acts involving the biogenesis and trafficking of molecular complexes of active zone material, the "trapping" or stabilization of active zone sites, and the subsequent development of mature synapses. Although the identities of proteins involved with establishing presynaptic specializations have been increasingly delineated, the exact functional mechanisms by which the active zone is assembled remain poorly understood. Here, we discuss a theoretical model for how the trapping stage of presynaptic differentiation might occur in developing neurons. We suggest that subsets of active zone proteins containing polyglutamine domains undergo concentration-dependent prion-like conversions as they accumulate at the plasma membrane. This conversion might serve to aggregate the proteins into a singular structure, which is then able to recruit scaffolding agents necessary for regulated synaptic transmission. A brief informatics analysis in support of this 'Q' assembly hypothesis--across commonly used models of synaptogenesis--is presented.

New insights regarding the cyclodextrin/AAS self-assembly: A molar ratio dependent system

The assembly between acetylsalicylic acid (AAS) and β-cyclodextrin (βCD), was characterized using NMR spectroscopy ( 1H, T 1, and NOESY), Isothermal Titration Calorimetry (ITC) and Static Light Scattering (SLS). NMR data showed the preferential orientation inside the cyclodextrin cavity, yet suggests the formation of high ordered complexes. Calorimetric titration showed a gradually less exothermic signal in an overall range of analyzed βCD concentrations, suggesting simultaneous aggregation and dessolvation of inclusion compounds. SLS data confirmed the self assembly hypothesis above 10 − 4 mM, bringing new insights regarding aggregation in cyclodextrin system, which could act as modulator of supramolecular structure of complex and consequently influence its use as control release system.

How is inflectional morphology learned?

This article considers recent explanations of variability in the second language (L2) comprehension of inflectional morphology. The predictions of five accounts are spelled out: the emergentist account, the Feature Assembly Hypothesis, the Contextual Complexity Hypothesis, the Morphological Underspecification Hypothesis and the Combinatorial Variability Hypothesis. These predictions are checked against the results of an experimental study on the L2 acquisition of inflectional morphology (based on an extension of Slabakova and Gajdos 2008). English-native learners of German at beginning and intermediate proficiency levels took a multiple-choice test where they had to supply appropriate missing subjects. The predictions of the Morphological Underspecification Hypothesis and the Combinatorial Variability Hypothesis were largely supported by the experimental findings. It is argued that only accounts looking at mental representation of lexical features adequately explain L2 morphological variability.

Functional trait assembly through ecological and evolutionary time

A classic community assembly hypothesis is that all guilds must be represented before additional species from any given guild enter the community. We conceptually extend this hypothesis to continuous functional traits, refine the hypothesis with an eco-evolutionary model of interaction network community assembly, and compare the resultant continuous trait assembly rule to empirical data. Our extension of the “guild assembly rule” to continuous functional traits was rejected, in part, because the eco-evolutionary model predicted trait assembly to be characterized by the expansion of trait space and trait/species sorting within trait space. Hence, the guild rule may not be broadly applicable. A “revised” assembly rule did, however, emerge from the eco-evolutionary model: as communities assemble, the range in trait values will increase to a maximum and then remain relatively constant irrespective of further changes in species richness. This rule makes the corollary prediction that the trait range will, on average, be a saturating function of species richness. To determine if the assembly rule is at work in natural communities, we compared this corollary prediction to empirical data. Consistent with our assembly rule, trait “space” (broadly defined) commonly saturates with species richness. Our assembly rule may thus represent a general constraint placed on community assembly. In addition, taxonomic scale similarly influences the predicted and empirically observed relationship between trait “space” and richness. Empirical support for the model’s predictions suggests that studying continuous functional traits in the context of eco-evolutionary models is a powerful approach for elucidating general processes of community assembly.

Testing for higher-order correlations in massively parallel spike trains

The cell assembly hypothesis [1] postulates dynamically interacting groups of neurons as building blocks of cortical information processing. Synchronized spiking across large neuronal groups was later suggested as a potential signature for active assemblies [2], resulting in specific higher-order correlations among assembly members. Mathematical concepts for the treatment of higher-order correlations in massively parallel spike trains have been suggested in the past, but, due to constraints of insufficient sample sizes, estimation of higher-order parameters from recorded data poses serious problems [3]. As a consequence, most attempts to detect active cell assemblies resort to pairwise interactions. However, pairwise approaches do not imply the presence of higher-order effects in large neuronal populations and are not sensitive for sparse synchronous events [4]. The limited experimental evidence in favor of the cell assembly hypothesis must to a large extent be assigned to the lack of suitable analysis tools [5]. Massively parallel extracellular recordings, in contrast, are nowadays widely available.

Learning-Induced Enduring Changes in Functional Connectivity among Prefrontal Cortical Neurons

Current thinking about how memories are stored in the brain has been profoundly influenced by Donald O. Hebb's cell assembly hypothesis, which posits that (1) learning produces a stable alteration in patterns of connectivity among repeatedly coactivated neurons, and (2) memory retrieval involves reactivation of those altered patterns of connectivity. However, learning-induced changes in connectivity that persist over long periods of time have not been clearly demonstrated. In the present study, two spatial navigation tasks and a long-term ensemble recording technique are used to describe long-lasting modifications in functional connectivity (FC) (defined as changes in synchronous firing) of prefrontal cortical neurons in behaving rats. Animals were initially trained to alternate visiting two spatial locations on a figure-8-shaped maze to obtain a reward (alternating task 1). Afterward, while continuing on task 1, animals were additionally trained to visit only one spatial location on the same maze to obtain a reward (unilateral task 2). Multiple single units were recorded while rats were undergoing acquisition, retention, and performance of both tasks. Our data indicate that correlated firing of prefrontal cortical neurons changed significantly in early phases of training when learning rate was maximal but became progressively smaller in later phases when learning reached asymptote. After animals became proficient, FC remained constant, although neuronal activities varied across two different tasks. The present finding of negatively accelerated changes in FC confirms associative learning theories and provides crucial neurophysiological evidence for Hebb's hypothesis.