Learning and memory: traditional and systems approaches

Determination of Neuronal Activity and Its Meaning for the Processes of Learning and Memory

Despite the years of studies in the field of systems neuroscience, the functions of neural circuits and behavior-related systems are still not entirely understood. The systems description of brain activity has recently been associated with cognitive concepts, e.g., a cognitive map, reconstructed via place-cell activity analysis and the like, and a cognitive schema, modeled in consolidation research. The issue we find of importance is that cognitive concepts reconstructed in neuroscience research are mainly formulated in terms of the environment. In this chapter, we present the idea of an element of individual experience that serves as a model of behavioral interaction with the environment, rather than a model of the environment itself. This intangible difference entails the need for substantial revision of several well-known phenomena, including long-term potentiation. The principal questions we address are: how do elements of experience appear and change during learning and performance; and how do the links between these elements create the whole structure of individual experience? We argue that learning and memory research need a clear distinction between processes that provide the emergence of new elements of experience (functional systems) and processes underlying the retrieval and/or changes in the existing experience. We propose to view the activity of a neuron as an "action" directed to the future adaptive "microresult," essential for meeting its metabolic needs. This anticipatory neuronal activity is coordinated with the activity of many other cells of the body in the organism-wide functional system, ensuring the achievement of an adaptive "macroresult" at the behavioral level. From this perspective, the mechanisms of learning are considered as the formation of functional systems, and memory is considered as a dynamic structure constituted by systems formed at different stages of individual development.

Neuronal metabolism in learning and memory: The anticipatory activity perspective

Current research on the molecular mechanisms of learning and memory is based on the "stimulus-response" paradigm, in which the neural circuits connecting environmental events with behavioral responses are strengthened. By contrast, cognitive and systems neuroscience emphasize the intrinsic activity of the brain that integrates information, establishes anticipatory actions, executes adaptive actions, and assesses the outcome via regulatory feedback mechanisms. We believe that the difference in the perspectives of systems and molecular studies is a major roadblock to further progress toward understanding the mechanisms of learning and memory. Here, we briefly overview the current studies in molecular mechanisms of learning and memory and propose that studying the predictive properties of neuronal metabolism will significantly advance our knowledge of how intrinsic, predictive activity of neurons shapes a new learning event. We further suggest that predictive metabolic changes in the brain may also take place in non-neuronal cells, including those of peripheral tissues. Finally, we present a path forward toward more in-depth studies of the role of cell metabolism in learning and memory.

Analytic and Holistic Thinkers: Differences in the Dynamics of Heart Rate Complexity When Solving a Cognitive Task in Field-Dependent and Field-Independent Conditions

Analytic and holistic thinking styles are known to be associated with individual differences in various aspects of behavior and brain activity. In this study, we tested a hypothesis that differences in thinking styles may also be manifested at the level of neuro-visceral coordination. Heart rate variability (HRV) was compared between analytic and holistic thinkers at rest, during a simple motor choice reaction time task and when solving cognitive choice reaction time tasks in conditions with varying instructions contrasting the role of the field when evaluating objects. Participants (N = 52) with analytic and holistic thinking styles were equally successful at solving the cognitive tasks but response times were longer in the analytic group, compared to the holistic group. Heart rate complexity, as measured by sample entropy, was higher in the analytic group during the cognitive tasks but did not differ from the holistic group at rest or during the simple motor task. Analytic participants had longer response times and higher heart rate complexity when evaluating objects in relation to the field than when evaluating objects irrespective to the field. No difference in response times or heart rate complexity between tasks was observed in the holistic group. Our findings demonstrate that differences in individual behavior, including those related to holistic and analytic thinking styles, can be reflected not only in brain activity, as shown previously using fMRI and EEG methods, but also at the level of neuro-visceral coordination, as manifested in heart rate complexity.

Regression II. Development through regression

As shown in our previous paper ('Regression I. Experimental approaches to regression', JAP, 65, 2, 345-65), the common mechanism of regression can be described as reversible dedifferentiation, which is understood as a relative increase of the proportion of low-differentiated (older) systems in actualized experience. Experimental data show that regression following disease (chronic tension headache) is followed by adaptation and an increase in system differentiation in that experience domain which contains systems responsible for that adaptation. The results of mathematical modelling support the idea that reversible dedifferentiation can be one of the mechanisms for increasing the effectiveness of adaptation through learning. Reversible dedifferentiation, which is phenomenologically described as regression, is a general mechanism for restructuring the organism-environment interactions in situations where behaviours that were effective in the past become ineffective. Reversible dedifferentiation has evolved as a component of adaptation when new behaviours are formed and large-scale modifications in the existing behaviours are required in the face of changes in the external and/or internal environment. Thus, the authors believe that this article provides evidence for Jung's view that regression is not only a 'return' to past forms of thinking, affects and behaviour, but that regressive processes provide a significant impetus for psychological growth and development.

Sample Entropy of the Heart Rate Reflects Properties of the System Organization of Behaviour

Cardiac activity is involved in the processes of organization of goal-directed behaviour. Each behavioural act is aimed at achieving an adaptive outcome and it is subserved by the actualization of functional systems consisting of elements distributed across the brain and the rest of the body. This paper proposes a system-evolutionary view on the activity of the heart and its variability. We have compared the irregularity of the heart rate, as measured by sample entropy (SampEn), in behaviours that are subserved by functional systems formed at different stages of individual development, which implement organism-environment interactions with different degrees of differentiation. The results have shown that SampEn of the heart rate was higher during performing tasks that included later acquired knowledge (foreign language vs. native language; mathematical vocabulary vs. general vocabulary) and decreased in the stress and alcohol conditions, as well as at the beginning of learning. These results are in line with the hypothesis that irregularity of the heart rate reflects the properties of a set of functional systems subserving current behaviour, with higher irregularity corresponding to later acquired and more complex behaviour.

Neuronal Bases of Systemic Organization of Behavior

Despite the years of studies in the field of systems neuroscience, functions of neural circuits and behavior-related systems are still not entirely clear. The systems description of brain activity has recently been associated with cognitive concepts, e.g. a cognitive map, reconstructed via place-cell activity analysis and the like, and a cognitive schema, modeled in consolidation research. The issue we find of importance is that a cognitive unit reconstructed in neuroscience research is mainly formulated in terms of environment. In other words, the individual experience is considered as a model or reflection of the outside world and usually lacks a biological meaning, such as describing a given part of the world for the individual. In this chapter, we present the idea of a cognitive component that serves as a model of behavioral interaction with environment, rather than a model of the environment itself. This intangible difference entails the need in substantial revision of several well-known phenomena, including the long-term potentiation.The principal questions developed here are how the cognitive units appear and change upon learning and performance, and how the links between them create the whole structure of individual experience. We argue that a clear distinction between processes that provide the emergence of new components and those underlying the retrieval and/or changes in the existing ones is necessary in learning and memory research. We then describe a view on learning and corresponding neuronal activity analysis that may help set this distinction.

Expression of c-Fos in the rat retrosplenial cortex during instrumental re-learning of appetitive bar-pressing depends on the number of stages of previous training

Learning is known to be accompanied by induction of c-Fos expression in cortical neurons. However, not all neurons are involved in this process. What the c-Fos expression pattern depends on is still unknown. In the present work we studied whether and to what degree previous animal experience about Task 1 (the first phase of an instrumental learning) influenced neuronal c-Fos expression in the retrosplenial cortex during acquisition of Task 2 (the second phase of an instrumental learning). Animals were progressively shaped across days to bar-press for food at the left side of the experimental chamber (Task 1). This appetitive bar-pressing behavior was shaped by nine stages (“9 stages” group), five stages (“5 stages” group) or one intermediate stage (“1 stage” group). After all animals acquired the first skill and practiced it for five days, the bar and feeder on the left, familiar side of the chamber were inactivated, and the animals were allowed to learn a similar instrumental task at the opposite side of the chamber using another pair of a bar and a feeder (Task 2). The highest number of c-Fos positive neurons was found in the retrosplenial cortex of “1 stage” animals as compared to the other groups. The number of c-Fos positive neurons in “5 stages” group animals was significantly lower than in “1 stage” animals and significantly higher than in “9 stages” animals. The number of c-Fos positive neurons in the cortex of “9 stages” animals was significantly higher than in home caged control animals. At the same time, there were no significant differences between groups in such behavioral variables as the number of entrees into the feeder or bar zones during Task 2 learning. Our results suggest that c-Fos expression in the retrosplenial cortex during Task 2 acquisition was influenced by the previous learning history.

Auditory cortex mapmaking: principles, projections, and plasticity

Maps of sensory receptor epithelia and computed features of the sensory environment are common elements of auditory, visual, and somatic sensory representations from the periphery to the cerebral cortex. Maps enhance the understanding of normal neural organization and its modification by pathology and experience. They underlie the derivation of the computational principles that govern sensory processing and the generation of perception. Despite their intuitive explanatory power, the functions of and rules for organizing maps and their plasticity are not well understood. Some puzzles of auditory cortical map organization are that few complete receptor maps are available and that even fewer computational maps are known beyond primary cortical areas. Neuroanatomical evidence suggests equally organized connectional patterns throughout the cortical hierarchy that might underlie map stability. Here, we consider the implications of auditory cortical map organization and its plasticity and evaluate the complementary role of maps in representation and computation from an auditory perspective.