Goal-seeking Behavior Research Articles

Late-term moderate prenatal alcohol exposure impairs tactile, but not spatial, discrimination in a T-maze continuous performance task in juvenile rats

Existing maze apparatuses used in rodents often exclusively assess spatial discriminability as a means to evaluate learning impairments. Spatial learning in such paradigms is reportedly spared by moderate prenatal alcohol exposure in rats, suggesting that spatial reinforcement alone is insufficient to delineate executive dysfunction, which consistently manifests in humans prenatally-exposed to alcohol. To address this, we designed a single-session continuous performance task in the T-maze apparatus that requires rats to discriminate within and between simultaneously-presented spatial (left or right) and tactile (sandpaper or smooth) stimuli for food reinforcement across four sequential discrimination stages: simple discrimination, intradimensional reversal 1, extradimensional shift, and intradimensional reversal 2. This design incorporates elements of working memory, attention, and goal-seeking behavior which collectively contribute to the executive function construct. Here, we found that rats prenatally-exposed to alcohol performed worse in both the tactile intradimensional reversal and extradimensional shift; alternatively, rats prenatally-exposed to alcohol acquired the extradimensional shift faster when shifting from the tactile to spatial dimension. In line with previous work, moderate prenatal alcohol exposure spared specifically spatial discrimination in this paradigm. However, when tactile stimuli were mapped into the spatial dimension, rats prenatally-exposed to alcohol required more trials to discriminate between the dimensions. We demonstrate that tactile stimuli can be operantly employed in a continuous performance T-maze task to detect discriminatory learning impairments in rats exposed to moderate prenatal alcohol. The current paradigm may be useful for assessing features of executive dysfunction in rodent models of fetal alcohol spectrum disorders.

Social capital in academia: Measuring researchers’ collaboration habits versus preferences

Abstract Many studies concerning social capital in academia have used social network theory and social network analysis as an approach. Social network analysis focuses on a boundary set of actors in a network and what it reveals as an outcome of social capital. However, social capital is also a precursor or catalyst for cooperative work. Here, we investigate researchers’ perceptions of social capital based on the hypothesis that what academics do when they collaborate (as a habit), may not relate to what they actually prefer. We have piloted a questionnaire-survey to test this, focusing on the goal-seeking behavior of publishing new research. Data were collected from 1,092 academics, across 6 faculties at the University of Copenhagen: Health and Medical Science, Science, Social Sciences, Humanities, Law, and Theology. The survey of collaboration habits first revealed significant differences at the level of gender, academic position, years active in publishing, and faculty. Collaboration preferences, interpreted from social capital theory, were also measured according to three interrelated dimensions—i.e. cognitive, relational, and structural. Survey respondents tended to prefer the cognitive-relational aspects of collaboration (i.e. reciprocity and obligation; shared understandings), over certain structural determinants (i.e. linking to networks). Few habits and preferences correlated and did not correlate strongly. Amongst the researchers who indicated a preference for bridging networks (i.e. working with people who have different types of expertise), few confirmed this as a collaboration habit, particularly with experts from organizations outside academia (i.e. the business/public sector).

IT-2 Fuzzy Control and Behavioral Approach Navigation System for Holonomic 4WD/4WS Agricultural Robot

In contemporary agriculture, researchers are focusing on precision farming and environmentally conscious techniques, leading to the advancement of autonomous agricultural mobile robots. Consequently, A navigation system using TSK Interval Type-2 fuzzy logic has been developed and, for the first time, applied to a holonomic mobile agricultural robot equipped with four-wheel drive and steer. This system employs a behavioral approach to accomplish the robot’s primary objective in unfamiliar environments. It comprises four controllers: one exclusively dedicated to goal-seeking behavior, with the remaining controllers responsible for obstacle avoidance. Supervision of these controllers is conducted through the Mandani fuzzy logic approach, which combines the outputs of all four controllers, robot wheel velocities and steering angles, using a proposed equations. Various case studies were examined and simulated utilizing MATLAB and VREP software platform to assess the navigator system’s performance. The simulation outcomes showcase the efficiency of the proposed equations and the system’s navigation capabilities. The stability of the entire system was thoroughly examined and confirmed, employing the Lyapunov function, in environments with and without obstacles.

Rice Self-Sufficiency Model to Enhance the Food Security Status in Nepal

The study focuses on the slow growth of rice production in Nepal and the country's heavy reliance on rice imports to meet its food demand. The government has been spending a significant portion of its budget on imports, and it aims to reduce this dependence by increasing domestic production and achieving food security goals. To understand the dynamics of this issue, system dynamics modelling steps were employed. The key variables considered in the model testing were domestic production, imports, per capita consumption, productivity per hectare, and average area expansion rate. The study utilized time series data from 1991 to 2020 and projected the analysis up to 2050 using Stella Architect, a computer-based software program. The findings reveal that both the population and imports have exhibited exponential growth over the years. The model also indicates goal-seeking behaviour, with the government setting targets for yield increment based on available harvest areas. However, the policies implemented thus far have mostly been quick-fix approaches focusing input subsidized programs. According to the model, an increase of 70-100% in rice production will be required by 2050 to meet the growing population's demand. The study presents three policy options for achieving rice self-sufficiency: 1) a 2% annual increase in average area expansion, 2) raising productivity from 3700 kg ha-1 to 5000 kg ha-1 and 3) increasing productivity to 3900 kg ha-1 while reducing per capita rice consumption from 200 kg to 130 kg. The study suggests that adopting the recommended policy implications can help increase rice production in Nepal. Decision-makers should adopt a dynamic approach to the rice production system to address the issue of slow growth and achieve national self-sufficiency and food security goals.

Subunit-selective PI3-kinase control of action strategies in the medial prefrontal cortex

PI3-kinase (PI3K) is an intracellular signaling complex that is stimulated upon cocaine exposure and linked with the behavioral consequences of cocaine. We recently genetically silenced the PI3K p110β subunit in the medial prefrontal cortex following repeated cocaine in mice, reinstating the capacity of these mice to engage in prospective goal-seeking behavior. In the present short report, we address two follow-up hypotheses: 1) The control of decision-making behavior by PI3K p110β is attributable to neuronal signaling, and 2) PI3K p110β in the healthy (i.e., drug-naïve) medial prefrontal cortex has functional consequences in the control of reward-related decision-making strategies. In Experiment 1, we found that silencing neuronal p110β improved action flexibility following cocaine. In Experiment 2, we reduced PI3K p110β in drug-naïve mice that were extensively trained to respond for food reinforcers. Gene silencing caused mice to abandon goal-seeking strategies, unmasking habit-based behaviors that were propelled by interactions with the nucleus accumbens. Thus, PI3K control of goal-directed action strategies appears to act in accordance with an inverted U-shaped function, with “too much” (following cocaine) or “too little” (following p110β subunit silencing) obstructing goal seeking and causing mice to defer to habit-like response sequences.

The Principle of Organization of Motivational Behavior and Automatic Goal Setting of Autonomous Intelligent Mobile Systems

The expediency of organizing the motivational behavior of autonomous intelligent mobile systems focused on solving various complex problems in unstable a priori undescribed problematic environments is substantiated. That need is due to the fact that this type of goal-seeking behavior allows intelligent systems of various purposes to ensure safe and efficient activity in unstable operating conditions. A model of knowledge representation of autonomous intelligent mobile systems is proposed without regard to a specific subject area and built on the basis of active fuzzy semantic networks. In such networks, vertices are labeled with slots that have many characteristics, which enables in the process of goal-seeking activity to label active vertices with objects and events occurring in the problematic environment that meet their requirements. Edges in such networks are labeled with generalized fuzzy values of corresponding conditions that must be met in a problematic environment between an autonomous intelligent mobile system, various objects, and occurring events. This model of a formalized description of various situations and subsituations of the problematic environment allows intelligent systems to adapt to a priori undescribed operating conditions and, on this basis, automatically plan goal-seeking activities under conditions of uncertainty. To control the motivational behavior and self-organization of autonomous intelligent mobile systems, tools have been developed intended to identify threats to productive activities that arise in a problematic environment. A generalized production-based model of knowledge representation has been built without regard to a specific subject area, which allows intelligent systems to quickly respond to various types of security threats that arise in a problematic environment and maintain operability in the process of performing complex tasks. In conclusion, one of the effective ways of further development of the proposed principle of organizing the safe and efficient operation of autonomous intelligent mobile systems is outlined, which is related to the management of their collective activities in the process of performing a complex task with changes occurring spontaneously in a problem environment, accompanied by the emergence of various types of threats in it that prevent their effective operation.

OPT-ing out: Root-shoot dynamics are caused by local resource capture and biomass allocation, not optimal partitioning.

Combining plant growth analysis with a simple model of local resource capture and biomass allocation applied to exemplary experimental data, showed that dynamic changes in allocation to roots when nutrients are scarce is caused by disparities in growth rates between roots and shoots. Whole-plant growth rates also change but are not caused by an adaptive allocation response. Allocation and whole-plant growth rate are interdependent, not independent, traits. Following a switch in nutrient availability or partial biomass removal, convergence of allocation and growth rate trajectories does not reflect goal-seeking behaviour, but the constraints imposed by finite resource availability. Optimal root-shoot allocations are unnecessary to maximise whole-plant growth rate. Similar growth rates are attainable with different allocations. Changes in allocation cannot maintain or restore a superior whole-plant growth rate. Roots and shoots do not have to be tightly coordinated but can operate semiautonomously, as their modular construction permits. These findings question the plausibility of the prevailing general explanation of plants'root-shoot allocation responses, 'optimal partitioning theory' (OPT). Local allocation models, not OPT, explain the origins of variability in root-shoot trade-offs in individuals, the allocation of biomass at global and ecosystem scalesand inform selection for allocation plasticity in crop breeding.

Basis and Principles of Systematic Thinking in Education

This research is a literature study that examines the basic principles and principles of systematic thinking in education. background of the need for systematic thinking in the world of education, the results of the study show that in systems thinking, this structure (a set of causal circles) determines the behavior (behavior or dynamics) of a phenomenon. A positive causal circle will result in a growth or decline behavior. Positive causal loops are also known as Reinforcing loop types or use the "R" notation. Meanwhile, a negative causal circle will result in a goal-seeking behavior, although sometimes the goals or objectives in the circle are not seen explicitly. The negative causal circle is also a balancing process using the notation "B".

Cell adhesion presence during adolescence controls the architecture of projection-defined prefrontal cortical neurons and reward-related action strategies later in life

Adolescent brain development is characterized by neuronal remodeling in the prefrontal cortex; relationships with behavior are largely undefined. Integrins are cell adhesion factors that link the extracellular matrix with intracellular actin cytoskeleton. We find that β1-integrin presence in the prelimbic prefrontal cortex (PL) during adolescence, but not adulthood, is necessary for mice to select actions based on reward likelihood and value. As such, adult mice that lacked β1-integrin during adolescence failed to modify response strategies when rewards lost value or failed to be delivered. This pattern suggests that β1-integrin-mediated neuronal development is necessary for PL function in adulthood. We next visualized adolescent PL neurons, including those receiving input from the basolateral amygdala (BLA) – thought to signal salience – and projecting to the dorsomedial striatum (DMS) – the striatal output by which the PL controls goal-seeking behavior. Firstly, we found that these projection-defined neurons had a distinct morphology relative to general layer V PL neurons. Secondly, β1-integrin loss triggered the overexpression of stubby-type dendritic spines at the expense of mature spines, including on projection-defined neurons. This phenotype was not observed when β1-integrins were silenced before or after adolescence. Altogether, our experiments localize β1-integrin-mediated cell adhesion within a developing di-synaptic circuit coordinating adaptive action

Seeking motivation and reward: Roles of dopamine, hippocampus, and supramammillo-septal pathway.

Reinforcement learning and goal-seeking behavior are thought to be mediated by midbrain dopamine neurons. However, little is known about neural substrates of curiosity and exploratory behavior, which occur in the absence of clear goal or reward. This is despite behavioral scientists having long suggested that curiosity and exploratory behaviors are regulated by an innate drive. We refer to such behavior as information-seeking behavior and propose 1) key neural substrates and 2) the concept of environment prediction error as a framework to understand information-seeking processes. The cognitive aspect of information-seeking behavior, including the perception of salience and uncertainty, involves, in part, the pathways from the posterior hypothalamic supramammillary region to the hippocampal formation. The vigor of such behavior is modulated by the following: supramammillary glutamatergic neurons; their projections to medial septal glutamatergic neurons; and the projections of medial septal glutamatergic neurons to ventral tegmental dopaminergic neurons. Phasic responses of dopaminergic neurons are characterized as signaling potentially important stimuli rather than rewards. This paper describes how novel stimuli and uncertainty trigger seeking motivation and how these neural substrates modulate information-seeking behavior.

Multimodal Integration Across Spatiotemporal Scales to Guide Invertebrate Locomotion.

Locomotion is a hallmark of organisms which has enabled adaptive radiation to an extraordinarily diverse class of ecological niches, and allows animals to move across vast distances. Sampling from multiple sensory modalities enables animals to acquire rich information to guide locomotion. Locomotion without sensory feedback is haphazard; therefore, sensory and motor systems have evolved complex interactions to generate adaptive behavior. Notably, sensory-guided locomotion acts over broad spatial and temporal scales to permit goal-seeking behavior, whether to localize food by tracking an attractive odor plume or to search for a potential mate. How does the brain integrate multimodal stimuli over different temporal and spatial scales to effectively control behavior? In this review, we classify locomotion into three ordinally ranked hierarchical layers that act over distinct spatiotemporal scales: stabilization, motor primitives, and higher-order tasks, respectively. We discuss how these layers present unique challenges and opportunities for sensorimotor integration. We focus on recent advances in invertebrate locomotion due to their accessible neural and mechanical signals from the whole brain, limbs, and sensors. Throughout, we emphasize neural-level description of computations for multimodal integration in genetic model systems, including the fruit fly, Drosophila melanogaster, and the yellow fever mosquito, Aedes aegypti. We identify that summation (e.g., gating) and weighting-which are inherent computations of spiking neurons-underlie multimodal integration across spatial and temporal scales, therefore suggesting collective strategies to guide locomotion.

Learning is shaped by abrupt changes in neural engagement.

Internal states such as arousal, attention and motivation modulate brain-wide neural activity, but how these processes interact with learning is not well understood. During learning, the brain modifies its neural activity to improve behavior. How do internal states affect this process? Using a brain-computer interface learning paradigm in monkeys, we identified large, abrupt fluctuations in neural population activity in motor cortex indicative of arousal-like internal state changes, which we term 'neural engagement.' In a brain-computer interface, the causal relationship between neural activity and behavior is known, allowing us to understand how neural engagement impacted behavioral performance for different task goals. We observed stereotyped changes in neural engagement that occurred regardless of how they impacted performance. This allowed us to predict how quickly different task goals were learned. These results suggest that changes in internal states, even those seemingly unrelated to goal-seeking behavior, can systematically influence how behavior improves with learning.

The PI3-Kinase p110β Isoform Controls Severity of Cocaine-Induced Sequelae and Alters the Striatal Transcriptome

BackgroundThe PI3-kinase (PI3K) complex is a well-validated target for mitigating cocaine-elicited sequelae, but pan-PI3K inhibitors are not viable long-term treatment options. The PI3K complex is composed of p110 catalytic and regulatory subunits, which can be individually manipulated for therapeutic purposes. However, this possibility has largely not been explored in behavioral contexts. MethodsHere, we inhibited PI3K p110β in the medial prefrontal cortex (mPFC) of cocaine-exposed mice. Behavioral models for studying relapse, sensitization, and decision-making biases were paired with protein quantification, RNA sequencing, and cell type–specific chemogenetic manipulation and RNA quantification to determine whether and how inhibiting PI3K p110β confers resilience to cocaine. ResultsViral-mediated PI3K p110β silencing reduced cue-induced reinstatement of cocaine seeking by half, blocked locomotor sensitization, and restored mPFC synaptic marker content after exposure to cocaine. Cocaine blocked the ability of mice to select actions based on their consequences, and p110β inhibition restored this ability. Silencing dopamine D2 receptor–expressing excitatory mPFC neurons mimicked cocaine, impairing goal-seeking behavior, and again, p110β inhibition restored goal-oriented action. We verified the presence of p110β in mPFC neurons projecting to the dorsal striatum and orbitofrontal cortex and found that inhibiting p110β in the mPFC altered the expression of functionally defined gene clusters within the dorsal striatum and not orbitofrontal cortex. ConclusionsSubunit-selective PI3K silencing potently mitigates drug seeking, sensitization, and decision-making biases after exposure to cocaine. We suggest that inhibiting PI3K p110β provides neuroprotection against cocaine by triggering coordinated corticostriatal adaptations.

Psychogenic theory of consciousness

The brain is a unique organization in nature, having the psychic activity, which is expressed in subjective states: thoughts, feelings, emotions. Knowledge of the nature of mental activity of the brain is the most urgent and the most challenging task of physiology. Historically the neurophysiology developed on the basis of physical and chemical laws discovered in an inanimate nature. Our investigation is devoted towards the origin of a human subjective state, and presents a new methodology for studying of the nature psychic brain activity. We have established the existence of physical phenomena unique for the living brain so-called «psychogenic field», which reflects the expressed psychic state of human brain. The subjective state of a human being was shown to affect remotely the physicochemical properties of the blood. An original schematic diagram is presented to describe the formation of the brain psychic activity. This approach is based on the feedback influence of a psychogenic field on neuronal molecular processes (self-induction in the brain). The paper describes the interrelation of neurophysiologic and subjective processes in the system organization of goal-seeking behavior. A «Psychogenic theory of consciousness» is proposed, suggests presuming the existence of physical phenomena unique for the living brain and brain fields, and their role in the origin of a subjective state.

Networks in the balance: an agent-based model of optimal exploitation

Using an agent-based simulation, we illustrate how goal-seeking behavior affects network formation, learning, and performance. Our organization has one manager, who decides where to invest financial capital; individual workers, who decide where to work and prefer projects with larger budgets; and projects, which vary in quality. Our manager discovers high-quality projects from interactions with workers and allocates more capital to high-quality projects. When given an opportunity, our workers move to bigger-budget projects. We let our manager vary in terms of how much she exploits what she learns and allow our workers vary in terms of how sensitive they are to differences in capital. Our results highlight a contingency which shapes how goal-seeking behavior affects learning. The contingency is network fragility. Fragile connections decay quickly when individuals are not working together, while robust relationships decay more slowly. When relationships are robust, exploitation by our manager leads to a dense organizational network, improving information quality, and performance. Decisions by self-interested individuals (our manager and our workers) produce a virtuous learning cycle. When relationships are fragile, exploitation by our manager produces a sparse network, reducing information quality, and undermining performance. When network connections are fragile, the manager must find the right balance of exploitation and exploration, a balance which limits the rate at which workers move from one project to the next, allowing the manager to exploit some of what she knows, without undermining the very network which allows for useful information to be obtained.

Разбиение сложных задач на подзадачи в процессе планирования целенаправленного поведения интегрального беспилотного летательного аппарата в пространстве состояний

Обозначены основные проблемы, связанные с разработкой интеллектуального решателя задач автоматической системы управления целенаправленным поведением интегрального беспилотного летательного аппарата в наземной проблемной среде. Рассмотрена конструкция типовых элементов представления знаний безотносительно к конкретной предметной области, позволяющих автономному беспилотному летальному аппарату, оснащенному манипулятором и системой технического зрения, решать сложные задачи в априори неописанных проблемных средах. Разработаны инструментальные средства разбиения сложных задач на подзадачи, обеспечивающие эффективный поиск их решения в пространстве состояний на основе типовых элементов представления знаний. Сформулированы основные методические положения, позволяющие синтезировать процедуры планирования целенаправленного поведения интегрального беспилотного летательного аппарата в сложных априори неописанных условиях функционирования. The main problems associated with the development of an intelligent problem solver of an automatic control system for the goal-seeking behavior of an integral unmanned aerial vehicle in a terrestrial problem environment are identified. The design of the typical elements of knowledge representation irrelative to the specific subject area is considered, allowing an autonomous unmanned aerial vehicle equipped with a manipulator and a vision system to solve complex problems in a priori undescribed problem environments. Tools are developed for partitioning complex tasks into sub-tasks, which provide an effective search for their solutions in the state space based on typical elements of knowledge representation. The main methodological provisions are formulated that allow synthesizing the planning procedures for the goal-seeking behavior of an integral unmanned aerial vehicle in a priori undescribed complex operating conditions.

Looking forward instead of backward

PurposeAccording to behavioral research, aspirations influence a firm's search – exploitive and explorative – for solutions that satisfy a firm's goals. Yet, such goal seeking behavior is adaptive to a firm's past experiences and not to a manager's expectations of its firm's future. A manager's expectations are often explained in terms of their confidence in future events. The purpose of this study is to address the following research question: how does a manager's confidence influence its expectations of a firm's future performance and goals; and how do these future expectations influence a firm's exploitive/explorative search?Design/methodology/approachIn drawing on cognition and legitimacy research, a conceptual model was developed to explain the antecedents and outcomes of a firm's “forward-looking” aspirations. The antecedents to a firm's forward-looking aspirations are attributed to a manager's overconfidence – anchoring, confirmation and availability – biases. In using strategic legitimacy explanations, these biases introduce distinct types of forward-looking (exploitive/explorative) search that legitimize/de-legitimize a manager's forward-looking aspirations.FindingsA key finding of this study is that it introduces a strategic decision-making process in which a firm's exploitive/ explorative search is adaptive toward its forward-looking aspirations.Research limitations/implicationsThis forward-looking strategic decision-making process offers research implications to understand how a firm's future goals and expectations can offer new understandings of their past experiences and traditions and explains how a manager's overconfidence biases can influence the assessment of a firm's social aspirational groups.Practical implicationsIn addition, this study also offers practical implications in which illustrative examples are used to explain this study's forward-looking strategic decision-making process.Originality/valueA distinct contribution of this study is that it introduces a forward-looking orientation that has not been previously examined the backward focus of behavioral research.

Living Apart Together? The Organization of Political Parties beyond the Nation-State: The Flemish Case

This article aims to contribute both theoretically and empirically to the study of political parties in the EU context, focusing on party organisation. Theoretically, it draws on insights from various literatures to develop a novel typology of multilevel party organisation specific to the EU context. It argues that parties are goal-seeking actors that choose their organisation based on a cost-benefit analysis, involving both party characteristics and the institutional context. Empirically, the article applies this framework on the Flemish political parties. It finds that rational goal-seeking behaviour cannot fully account for parties’ organisational choices. Results show that normative and historical considerations play a crucial role in parties’ cost-benefit analysis. It therefore calls upon future research to expand the number of comparative studies and to further assess parties’ goal-seeking behaviour regarding their multilevel organisation.

Model of Representation and Acquisition of New Knowledge by an Autonomous Intelligent Robot Based on the Logic of Conditionally Dependent Predicates

The model for the representation of declarative and procedural knowledge of an autonomous intelligent robot is developed without reference to a specific subject area. The logic of conditionally dependent predicates underlies the construction of this model. Procedures that allow an autonomous intelligent robot to automatically generate new knowledge needed for a readout in the process of planning goal-seeking behavior in undetermined conditions of a problem-solving environment are proposed. The method of proving the satisfiability of the formulas under the logic of conditionally dependent predicates with linear complexity is based on the attribution of object variables in them as objects of the problem-solving environment and serves to process knowledge that is used by an autonomous intelligent robot to automatically build plans for goal-seeking behavior under undetermined operating conditions.

OIL SPILL RESPONSE PREPAREDNESS MODEL THROUGH COMMUNITY PARTICIPATION IN TELUK PENYU BEACH, CILACAP REGENCY

In Indonesia, oil spill incidents often occur; thus, it has become a matter of national concern. Cilacap Regency is one of the regions in Indonesia that is prone to oil spills, with a history of frequent oil spill incidents during 2000–2018. Oil spill response preparedness needs the integrated effort between government and communities to minimize the environmental impacts of oil spills. A problem usually encountered is the lack of integration of community participation in the oil spill contingency plan because of the limited knowledge of the community regarding oil spill response preparedness. This study aimed to build an oil spill response preparedness model through community participation in Teluk Penyu Beach, Cilacap Regency. This study used the system dynamics modeling method. Results showed that the oil spill volumes in the waters (decay behavior) and on the beach (goalseeking behavior) rapidly decreased after 240 h (10 days). In conclusion, oil spill response preparedness needs the integration between company and community participation by increasing knowledge through community involvement in a combination of oil spill response exercises.