1,721,290 research outputs found
Situating CIS – The importance of Context in Collaborative Information Seeking
No full textCollaborative Information Seeking (CIS) is common in many professional contexts. This chapter discusses CIS from four different perspectives – education, healthcare, science research and patent research. We first introduce the CIS context, focusing on Evans and Chi’s proposed model of social search. We highlight the ways contextual factors relate to the search process, in particular noting the role of communication in CIS processes. The four example professional contexts are discussed with reference to the ‘medium’ of collaboration, the ways CIS is conducted, the tools used and physical setting of CIS, and the ‘context’ of CIS, the purposes for which an instance of CIS occurs in that discipline. We suggest that these contextual factors can be aligned with, but are additional to, the existing Evans and Chi model of social search, and that their addition in a ‘pre- and post-model’ extension could provide a shared framework for researching contextual features of CIS. In highlighting commonalities and contrasts across the disciplinary contexts we suggest that a developed model, and further research, is needed to understand the relationship between motivations in these different disciplines and the evaluation of CIS episodes, and the role of processes, particularly communication, in those episodes. In order to evaluate CIS in different disciplines future research should focus on the between, and within discipline differences in the purposes of CIS. Characteristics of success in different disciplinary contexts may relate both to the consideration of the collaborative context, and the information need; developing deeper understanding of this point
Digital Collaborative Mapping Tools for Engaging Residents in Placemaking
No full textThe main objective of this chapter is to present and assess research approaches designed to involve urban residents in placemaking processes. A critical examination of these research approaches, which utilise digital collaborative mapping tools to engage residents and gather data on their perceptions of public places in urban environments, reveals their potential to support subsequent placemaking efforts. Through three case studies we mainly demonstrate how these research approaches, based on the use of digital collaborative mapping tools, can engage people and encourage them to share their perceptions of public places. We show the data these approaches provide and, more broadly, how the data impact placemaking. The first case study, conducted in Olomouc (Czech Republic), utilised mental mapping to identify public places where residents experience fear of crime. The survey employed a computer-assisted web interviewing method to engage local residents in data collection. The second study, conducted in Vienna (Austria), aimed to explore how perception influences navigation choices, in order to enhance route-planning services. The EmoMap project developed a digital system to collect affective evaluations of the environment as a means of understanding how these evaluations influence people’s navigation decisions. The third case study presents research conducted in Bergamo (Italy), where perception was methodologically used to explore the “happy relationship” between inhabitants and places. The Happy Places digital consultation system was employed to identify common traits shared by various places, based on people’s experiences. Despite the different spatial contexts and methodological limitations of the evaluated approaches, our findings demonstrate the importance of digital tools for engaging communities in the processes involved in the transformation and sustainable development of urban environments. In this sense, digital collaborative mapping tools represent an opportunity for future efforts to capture data concerning the knowledge of local residents.
Only by using this data can the reproduction and transformation of the urban environment be effectively and sustainably planned to best meet the needs of its users
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
A neural model of decision making
Full text linkBackground: A descriptive neuroeconomic model is aimed for relativity of the concept of economic man to empirical science.Method: A 4-level client-server-integrator model integrating the brain models of McLean and Luria is the general framework for the model of empirical findings.Results: Decision making relies on integration across brain levels of emotional intelligence (LU) and logico-matematico intelligence (RIA), respectively. The integrated decision making formula approaching zero by bottom-up emotional and frontoparietal-downward logico-matematico learning is:CONC := LU-RIAConclusion: The model is validated as a prototype of a socioeconomic decision-maker instead of a classical Robinson Crusoe pursuing self interest, only, as: 1) The Ultimatum game generates a simultaneous activity in both the LU and the RIA complexities as characteristic to classical economic man2) L is sensitive to social rewards as equality, participation, trust and reputation which enlarge economic man with active social preferences. However, a typical pessimistic mood biases decisions for immediate instead of long termed solutions as indicated by various game trials represents a serious barrier to long term planning. The findings on human-relations-efficacy and simple de-stressing techniques might be relevant to coaching in post-industrial conditions of networking across hierarchical organisations, especially. 1 BACKGROUNDEconomic psychology is based on a rather simple paradigm of economic man pursuing his best self-interest using reasoning to adapt to the conditions of life i.e. a budget restriction as traced back to Pareto 1906. To illustrate the paradigm of economic man economists often refer to Robinson Crusoe living a simple and isolated life on a small island in the 1719-novel of Daniel Defoe. However, in the last decade neuroimaging technologies have become that sensitive that the activity of small groups of nerve cells may be detected i.e. by functional magnetic resonance tomography (fMRI). fMRI tracks blood flow in the brain using changes in magnetic properties due to the blood-oxygen-level (BOLD signal). This enables the detection of neural activity during ordinary thinking, feeling and decision-making which are much more subtle than the neural dysfunction detected by the Electroencephalogram (EEG). A limitation of fMRI is the lack of distinction between facilitating and inhibitory processes and EEG is still useful for research as a broader and direct measure of brain activity. On this background a new interdisciplinary field linking behavioural economics and neuroscience into a neuroeconomic discipline emerges. Recent reviews of neuroeconomics represent a platform for further development of neuroeconomics [McLean 1992 and Luria 1973]. An overview of neuroeconomics from an economic perspective reviewing 13 studies [Kenning and Plassman, 2005]. It is concluded that the first studies are explorative research focusing concepts crucial to modern economic theory such as fairness, trust, altruism, memory, learning and knowledge. The goal of neuroeconomics is stated as to provide a descriptive decision-making theory, which is not restricted to economic theory and more realistic than that of economic man. Reviewing how neuroscience can inform economics [Camerer et al., 2005]. A schematic framework with the dimensions cognitive-affective and automatic-controlled processes is advanced, where Fig. 1 indicates that this might be summarized as a dynamic interaction between automatic bottom-up affects from the midbrain and cognitive top-down control from the prefrontal cortex. The present study aims to provide the aimed descriptive decision-making model [Kenning and Plassmann, 2005] departing from the proposed 2-dimensional reference scheme [Camarer et al, 2005]. 2 METHODRecent neurobiology has two parallel lines of research on the general structure of the central nervous system (CNS). One line of research is based on biochemical trials reflecting phylogenesis [McLean, 1992]. The other line of research referring to ‘Working Brain Model' [Luria, 1973] is based on direct observation of the specific functional deficit associated with specific brain damages operate with three separate brain units, too. However, the subdivisions of the two models combine to a CNS with four levels reflecting phylogenesis. A four level CNS model is proposed as a Conflict Systems Neurobehavioral model [Cory and Gardner, 2002, Ch. 18]. However, this model presents itself as subjective/ behavioural rather than neurophysiological with ‘blackboxes' which is difficult to falsify for further development. In client-server programs the client requests services from the server, which responds to the request. As the brain contains more specialized servers an integrator is required to integrate the different servers (cybernetics of the second order). The framework is an integration of the models of McLean and Luria at four brain levels: L1. Instincts (Client) as the Reptile complex in McLean L2. Emotions (Client server) as Mammalian complex (Limbic System) in McLean L3. Cognition serves the perception-storage unit 2 in Luria L4. The Executive (Servers of integrator) as the frontal unit 3 in Luria The operation of the different levels is based on a 2-stage literature search in Medline for neuroeconomic studies since 2000. The search is terminated ultimo 2007. In all, 57 neuroeconomic studies are identified. Hereof are 15 reviews and 16 empirical studies considered for the neuroeconomic model of which 6 relate directly to the model. This specific neuroeconomic search is complemented by Medline search for trials specific to the decision-making variables as specified in table 1. In this way about 30 empirical studies of basal neuroscience are included as the major part of the neuroeconomic knowledgebase.3.1 PARTIAL RESULTS (Variables)3.1.1 Instincts (L1)Reticular ascending activation system in the brain stem (RAS) as clientRAS is well documented as the ‘Energizer' of the CNS since 1949. Representing the Reptile level of the brain the behavioural pattern of RAS is the fight-or-flight-response [McLean, 1992]. Higher brain levels serve to improve the coordination of behaviour. The galvanic skin response measures the level of Sympaticus activation by RAS where electrodermal activity is recognized as a valid neural indicator among different variants of electrical skin indices [Critschley, 2002]. 3.1.2 Emotions (L2) Primary consciousness in anterior cingulate cortex (PC)Emotions are hypothesized to serve as ‘somatic-markers' [Bechara et al, 2000] informing the client on the over-all situation of the body as well as transmitting this information upward for further cortical processing. Emotions are generated within ‘Papez circuit' (1937) from 1) Hippocampus, via 2) Hypothalamus, to 3) Thalamus, towards the 4) Anterior Cingulate (ACC) and back.1. The role of Hippocampus in the formation of episodic or autobiographical memories is unquestioned (M). A newer line of Hippocampal research focuses the branching between ‘familiar' and ‘novel' sensory input.‘Novel'-perceptions arising from mismatch with existing memories mobilizes the basal flight-or-fight response upward via the posterior cingulated towards the ventromedial prefrontal cortex (the reversal pathway serves recall of M).‘Familiar'-perceptions suspend the fight-or-flight response for processing in ‘Papez circuit', see figure 1.The activity balance between the left and right arm of Hippocampus indicates the balance between ‘familiar' and ‘novel' activity [Kumaran and McGuire, 2007].2. Hypothalamus is centre of autonomic homeostasis (H) which is standard knowledge. 3. Thalamus generates cortical synchrony (α%) [Hanslmeyr et al, 2007].4. The ACC is identified as a primary centre of consciousness (PC) transmitting upward signals by 2 different pathways in a reciprocal relationship [Mohanty et al and Margulies et al, 2007]. In all, the original Mcleanian hypothesis of a primary self in the ACC is confirmed:The rostral ACC transmits emotional signals towards the orbitofrontal cortex which is essential for learning the values of actions [Kennerley et al, 2006] and has empathic properties [Singer, 2006]. Furthermore, the Insula is evidenced as important to addiction i.e. nicotine [Naqvi et al, 2007] defending PC [Wendt et al, 2007] in that way that sensory input elicits fear of missing the reward before the reward giving action is executed [Yeung and Sanfey, 2004]. Thus, Insula is a primary reward server to Papez circuit (Is)The caudal ACC transmits cognitive information (associations) towards the frontoparietal lobes [Mohanty et al 2005 and Margulies et al 2007]Moreover, the Posterior Cingulate Cortex represents a third pathway towards the visual association centre in the occipital lobes for mismatches detected at the level of Hippocampus [Kounios, 2006]Papez circuit modify instinctive fight-or-flight freezing-for-emotional reset. The complexity of ‘Papez circuit' including the Is originating our primary consciousness is determined by the equation:PC = M*H* α%*Is Limbic system as integrated neuroendocrine unit of homeostasis (L) Nearly hundred years ago Thorndike (1911) formulated the Law of effect postulating that a reward i.e. food increases the frequency and intensity of a specific behaviour leading to the reward. This basic law of learning has a neurochemical correlate in what has been termed the dopaminergetic reward system [Schultz, 2006]. The core of this system is a mesolimbic dopamine circuitry (D) which modulates voluntary movement by motivation in learning as well as decision-making while the Niagro-striatal circuit is involved in learning, storing and expression of habits. The dynamics of the motivational rewards relies on the ‘SEEKING system Hypothesis' [Alcaro, 2007]. D interacts closely with other cortical neurotransmitters as Serotonin (memory, emotions, wakefulness, sleep and temperature regulation) and GABA (Inhibition of motor neurons). The complex of interrelated neurotransmitters with the SEEKING-Disposition as a key factor is regulated by H. Moreover, H regulates peripheral endocrine glands by the neuroendocrine axis between Hypothalamus and the Pituary gland. D is stressed by excessive cortisol [Takahashi et al, 2004] wherefore the reciprocal of the concentration of plasma cortisol indicates the strength of D. Server 1 combines D and PC having a common integrator in Hypothalamus (H) into an integrated neuroendocrine unit of homeostasis termed Limbic system (L) by McLean, see figure 1. L serves as a Mammal freezing-for-emotional reset complex modifying the basal fight-or-flight response (RAS) by learning. As a self-sustaining system the 3-channel and 2-way upward impact of L is determined as the first derivative with respect to RAS: (S1) L = d(PC*D)/dRAS 3.1.3 Cognition (L3)Semantic memory recall in superior temporal sulcus (R)The Semantic Recollection (R) as associated with activity in the primary auditory cortex (Superior Temporal Sulcus, STS) is measured by theta-activity (Φ) in the EEG (in a range of 4-7 Hz) [Sauseng et al, 2006]. See, elaborated description at L4.Thalamo-cortico integrationThe characteristic resting pattern of the brain is α-waves in the 8-12 Hz/s band which indicates an autogenic cortical reset originated in Thalamus (α%) [Hanslmayr et al, 2007]. The dynamics of the associative cortices arising from PC is characterized by a polarization in between affective emotions (Rostral ACC), cognitive information (Caudal ACC) and mismatch by the Posterior Cingulate. Eventual Neocortical integration (AHA-experiences) has two different patterns: Firstly, one type of AHA-experience is identified as related to increased activity in medial frontal areas associated with voluntary activity and in temporal areas associated with semantic processing as expected from cognitive control. Secondly, a spontaneous (unprepared) AHA-experience of similarity-associations involving PC is identified as characterized by increased occipital activity consistent with integration of mismatched perceptions. To facilitate thalamo-cortico integration (AHA-experiences) we might rely on either frontoparietal cognitive control manipulating M or spontaneous integration by α%. The relevant servers involving the executive level are specified in section L4.3.1.4 The Executive (L4)A series of fMRI-studies evidence a tripartite structure of the frontal cortex:Logical analysis by the dorsolateral prefrontal cortex (A)The dorsolateral prefrontal cortex (dlPFC) which is the most recent phylogenetic step of evolution is an analyst with R as an important server [Robertson et al, 2001]. The cognitive control is specified in accordance with the Working Memory Model [Baddeley, 2002]: dlPFC is the executive centre of the phonological loop (A)STS is centre of the phonological loop operating RThe intraparietal sulcus, which is involved in numerical calculation [Cantlon et al, 2006], represents the visuospatial sketchpad (I) serving the integration of new perceptions in the phonological loop by AHA-experiencesCerebellum serves R with buffer relations to M i.e. coordination of walking.Server 2 refers to a frontal-parietal-downward logico-matematico intelligence centred in dlPFC which serves to sequence semantic memories [Robertson et al, 2001]:(S2) RIA Utility centre in the orbitofrontal cortex (U)The orbitofrontal cortex (OFC) receives emotional information from both Striatum, L and neocortical centres in the D [Alcaro, 2007]. An internal control centre in the left lateral part of the OFC accomplishes the integration of emotion and cognition suppressing emotions for cognitive analysis [Beer et al, 2007]. Such gradient of the present level of valence is anticipated in the classical economic concept of ranked utility []. A special fMRI-study by non-verbal cartoon tasks does not involve the dlPFC [Völlm et al, 2006]. It demonstrates that the ventromedial PFC manipulates emotions voluntarily independent of L and RAS. Server 3 is a bottom-up emotional intelligence from L towards the OFC [Wallis, 2007]. This LU-function is localized as the active centres during dreaming when the RIA is sleeping [Muzur et al, 2002]:(S3) LUPower of concentration (CONC) in the ventromedial prefrontal cortex (vmPFC)The vmPFC is crucial for frontal integration minimizing prediction errors [Schultz 2006 and Oya et al 2005]. This is achieved by voluntary emotional control of LU for cognitive analysis by RIA as the core function of CONC [Beer et al, 2007].3.2 INTEGRATED RESULTS3.2.1 The over-all modelThe major finding is that four phylogenetic subdivisions of the brain (L1-4) interact as a whole across levels in decision making. The neuroeconomic decision making formula combines S2 and S3 in a bottom-up - frontoparietal-downward learning process minimizing the error between expected and realized utilities (Non-integrated mismatches are preserved in the occipital lobes for delayed integration): CONC := LU-RIA Figure 2 shows the flowchart constituting CONC. Variables are summarized in table 1. Specificity, sensitivity and predictive value of the model are validated below.3.2.2 SpecificityA prototype of neuroeconomic fMRI-studies is the Ultimatum Game where the buyer can reject an offer i.e. an amount of money. If the buyer rejects both players receive nothing. The Ultimatum Game is correlated with a simultaneous brain activity in dlPFC (RIA) and ACC/Is (LU) [Sanfey et al, 2003] or both the complexities constituting CONC. This is indicates economic choices (maximizing utility by rational analysis) as a prototype of neurobiological decision-making. In all, the state of decision-making integrates two specialized mental states: the specific state of logico-mathematico learning characterized by significant MRI-activity in RIA [Robertson et al, 2007] and the specific state of emotional learning or ‘emphathizing' characterized by significant MRI-activity in LU [Singer 2006 and Völlm et al 2007]; As an opposite to the state of decision making relaxation serves an autonomic mental resetting with α-waves in the EEG [18].3.2.3 SensitivityFunctions commonly involved in social decision-making as specified in a review [Sanfey, 2007] serve as a checklist of the sensitivity of the model, see figure 4. All functions identified by Sanfey are included in our model, too. Moreover, 1) Hippocampus relevant to social perception, 2) Intraparietal Sulcus serving calculation and 3) the occipital visual association centre serving a delayed integration of mismatches are explicitly specified in our model. Regarding economic preferences other game-studies i.e. Prisoners Dilemma (PD) where each of two players makes one of two choices: cooperate or defect. More variants of PD have identified responses in both Insula and Striatum (L2) giving evidence to a social dimension in human decision-making [Fehr and Camerer, 2007]. A review of the insights in social decision-making from game theory and neuroscience concludes that neural correlates are evidenced for social values as reputation, trust, equality and cooperation [Sanfey, 2007]. In all, the neoclassical dogma of economic man pursuing a ‘bounded rationality' [Simon, 1978] is enlarged with an active social dimension.3.2.4 Predictive valueThe balance of emotional signals (LU) and logical analysis (RIA) as determined by CONC (prediction function) is a balance between expected and realized utility. Besides factual information this balance depends on the general state of mind or mood as determined by D in L. The behavioural significance of the mood is well-known to economists as closely related to the general business cycle: optimism enhances business while pessimism is associated with recession. A probabilistic study of economic choices finds a human bias towards risk and uncertainty [Takahashi, 2007] indicating a pessimistic mood. This finding is explained by the negative character of L-arousal [Yeung and Sanfey, 2004] mobilizing fear to miss a reward which is responded by CONC arousing fear to make errors. So, the typical relationship between the limbic system and Neocortex is indicated as an unsteady balance based on mutual fear which in both circuits are aroused by Amygdala. However, a minority of mankind is risk takers (optimists) exploring new possibilities. The interaction between the majority of risk-averters and a minority of risk-taking entrepreneurs explains the economic growth related to industrialization. Yet, the typical pessimistic mood explains an evidenced bias favouring immediate instead of future rewards more than justified by rational discounting [Loewenstein et al, 2008]. A serious affective barrier against long term planning in the post-industrial societies facing ecological challenges!4 DISCUSSION OF PALEO-NEOCORTICO INTEGRATIONFor neuroscience the close interaction between paleo- (limbic) and neocortical levels by three different pathways for emotional, associative and mismatches, respectively, indicates an upgrade of the autonomic nervous system from a subcortical somatic automatism to a primary centre of consciousness in ACC (L). The recognition of L demands a revision of some clinical protocols in the borderline between pharmaceutical and therapeutical interventions. However, at this stage the focus is the possibilities to improve CONC improving the general mood:1. Better satisfaction of the social preferences in L improves social learning in general and work group productivity in particular. Specific, the evidenced efficacy of human relations management of work groups known as the Hawthorne-effect [Mayo, 1949] is explained by the model as reduction of the negative valence of L. Recently, this mechanism is rediscovered in healthcare as a domina
A neural model of decision making
Full text linkBackground: A descriptive neuroeconomic model is aimed for relativity of the concept of economic man to empirical science.Method: A 4-level client-server-integrator model integrating the brain models of McLean and Luria is the general framework for the model of empirical findings.Results: Decision making relies on integration across brain levels of emotional intelligence (LU) and logico-matematico intelligence (RIA), respectively. The integrated decision making formula approaching zero by bottom-up emotional and frontoparietal-downward logico-matematico learning is:CONC := LU-RIAConclusion: The model is validated as a prototype of a socioeconomic decision-maker instead of a classical Robinson Crusoe pursuing self interest, only, as: 1) The Ultimatum game generates a simultaneous activity in both the LU and the RIA complexities as characteristic to classical economic man2) L is sensitive to social rewards as equality, participation, trust and reputation which enlarge economic man with active social preferences. However, a typical pessimistic mood biases decisions for immediate instead of long termed solutions as indicated by various game trials represents a serious barrier to long term planning. The findings on human-relations-efficacy and simple de-stressing techniques might be relevant to coaching in post-industrial conditions of networking across hierarchical organisations, especially. 1 BACKGROUNDEconomic psychology is based on a rather simple paradigm of economic man pursuing his best self-interest using reasoning to adapt to the conditions of life i.e. a budget restriction as traced back to Pareto 1906. To illustrate the paradigm of economic man economists often refer to Robinson Crusoe living a simple and isolated life on a small island in the 1719-novel of Daniel Defoe. However, in the last decade neuroimaging technologies have become that sensitive that the activity of small groups of nerve cells may be detected i.e. by functional magnetic resonance tomography (fMRI). fMRI tracks blood flow in the brain using changes in magnetic properties due to the blood-oxygen-level (BOLD signal). This enables the detection of neural activity during ordinary thinking, feeling and decision-making which are much more subtle than the neural dysfunction detected by the Electroencephalogram (EEG). A limitation of fMRI is the lack of distinction between facilitating and inhibitory processes and EEG is still useful for research as a broader and direct measure of brain activity. On this background a new interdisciplinary field linking behavioural economics and neuroscience into a neuroeconomic discipline emerges. Recent reviews of neuroeconomics represent a platform for further development of neuroeconomics [McLean 1992 and Luria 1973]. An overview of neuroeconomics from an economic perspective reviewing 13 studies [Kenning and Plassman, 2005]. It is concluded that the first studies are explorative research focusing concepts crucial to modern economic theory such as fairness, trust, altruism, memory, learning and knowledge. The goal of neuroeconomics is stated as to provide a descriptive decision-making theory, which is not restricted to economic theory and more realistic than that of economic man. Reviewing how neuroscience can inform economics [Camerer et al., 2005]. A schematic framework with the dimensions cognitive-affective and automatic-controlled processes is advanced, where Fig. 1 indicates that this might be summarized as a dynamic interaction between automatic bottom-up affects from the midbrain and cognitive top-down control from the prefrontal cortex. The present study aims to provide the aimed descriptive decision-making model [Kenning and Plassmann, 2005] departing from the proposed 2-dimensional reference scheme [Camarer et al, 2005]. 2 METHODRecent neurobiology has two parallel lines of research on the general structure of the central nervous system (CNS). One line of research is based on biochemical trials reflecting phylogenesis [McLean, 1992]. The other line of research referring to ‘Working Brain Model' [Luria, 1973] is based on direct observation of the specific functional deficit associated with specific brain damages operate with three separate brain units, too. However, the subdivisions of the two models combine to a CNS with four levels reflecting phylogenesis. A four level CNS model is proposed as a Conflict Systems Neurobehavioral model [Cory and Gardner, 2002, Ch. 18]. However, this model presents itself as subjective/ behavioural rather than neurophysiological with ‘blackboxes' which is difficult to falsify for further development. In client-server programs the client requests services from the server, which responds to the request. As the brain contains more specialized servers an integrator is required to integrate the different servers (cybernetics of the second order). The framework is an integration of the models of McLean and Luria at four brain levels: L1. Instincts (Client) as the Reptile complex in McLean L2. Emotions (Client server) as Mammalian complex (Limbic System) in McLean L3. Cognition serves the perception-storage unit 2 in Luria L4. The Executive (Servers of integrator) as the frontal unit 3 in Luria The operation of the different levels is based on a 2-stage literature search in Medline for neuroeconomic studies since 2000. The search is terminated ultimo 2007. In all, 57 neuroeconomic studies are identified. Hereof are 15 reviews and 16 empirical studies considered for the neuroeconomic model of which 6 relate directly to the model. This specific neuroeconomic search is complemented by Medline search for trials specific to the decision-making variables as specified in table 1. In this way about 30 empirical studies of basal neuroscience are included as the major part of the neuroeconomic knowledgebase.3.1 PARTIAL RESULTS (Variables)3.1.1 Instincts (L1)Reticular ascending activation system in the brain stem (RAS) as clientRAS is well documented as the ‘Energizer' of the CNS since 1949. Representing the Reptile level of the brain the behavioural pattern of RAS is the fight-or-flight-response [McLean, 1992]. Higher brain levels serve to improve the coordination of behaviour. The galvanic skin response measures the level of Sympaticus activation by RAS where electrodermal activity is recognized as a valid neural indicator among different variants of electrical skin indices [Critschley, 2002]. 3.1.2 Emotions (L2) Primary consciousness in anterior cingulate cortex (PC)Emotions are hypothesized to serve as ‘somatic-markers' [Bechara et al, 2000] informing the client on the over-all situation of the body as well as transmitting this information upward for further cortical processing. Emotions are generated within ‘Papez circuit' (1937) from 1) Hippocampus, via 2) Hypothalamus, to 3) Thalamus, towards the 4) Anterior Cingulate (ACC) and back.1. The role of Hippocampus in the formation of episodic or autobiographical memories is unquestioned (M). A newer line of Hippocampal research focuses the branching between ‘familiar' and ‘novel' sensory input.‘Novel'-perceptions arising from mismatch with existing memories mobilizes the basal flight-or-fight response upward via the posterior cingulated towards the ventromedial prefrontal cortex (the reversal pathway serves recall of M).‘Familiar'-perceptions suspend the fight-or-flight response for processing in ‘Papez circuit', see figure 1.The activity balance between the left and right arm of Hippocampus indicates the balance between ‘familiar' and ‘novel' activity [Kumaran and McGuire, 2007].2. Hypothalamus is centre of autonomic homeostasis (H) which is standard knowledge. 3. Thalamus generates cortical synchrony (α%) [Hanslmeyr et al, 2007].4. The ACC is identified as a primary centre of consciousness (PC) transmitting upward signals by 2 different pathways in a reciprocal relationship [Mohanty et al and Margulies et al, 2007]. In all, the original Mcleanian hypothesis of a primary self in the ACC is confirmed:The rostral ACC transmits emotional signals towards the orbitofrontal cortex which is essential for learning the values of actions [Kennerley et al, 2006] and has empathic properties [Singer, 2006]. Furthermore, the Insula is evidenced as important to addiction i.e. nicotine [Naqvi et al, 2007] defending PC [Wendt et al, 2007] in that way that sensory input elicits fear of missing the reward before the reward giving action is executed [Yeung and Sanfey, 2004]. Thus, Insula is a primary reward server to Papez circuit (Is)The caudal ACC transmits cognitive information (associations) towards the frontoparietal lobes [Mohanty et al 2005 and Margulies et al 2007]Moreover, the Posterior Cingulate Cortex represents a third pathway towards the visual association centre in the occipital lobes for mismatches detected at the level of Hippocampus [Kounios, 2006]Papez circuit modify instinctive fight-or-flight freezing-for-emotional reset. The complexity of ‘Papez circuit' including the Is originating our primary consciousness is determined by the equation:PC = M*H* α%*Is Limbic system as integrated neuroendocrine unit of homeostasis (L) Nearly hundred years ago Thorndike (1911) formulated the Law of effect postulating that a reward i.e. food increases the frequency and intensity of a specific behaviour leading to the reward. This basic law of learning has a neurochemical correlate in what has been termed the dopaminergetic reward system [Schultz, 2006]. The core of this system is a mesolimbic dopamine circuitry (D) which modulates voluntary movement by motivation in learning as well as decision-making while the Niagro-striatal circuit is involved in learning, storing and expression of habits. The dynamics of the motivational rewards relies on the ‘SEEKING system Hypothesis' [Alcaro, 2007]. D interacts closely with other cortical neurotransmitters as Serotonin (memory, emotions, wakefulness, sleep and temperature regulation) and GABA (Inhibition of motor neurons). The complex of interrelated neurotransmitters with the SEEKING-Disposition as a key factor is regulated by H. Moreover, H regulates peripheral endocrine glands by the neuroendocrine axis between Hypothalamus and the Pituary gland. D is stressed by excessive cortisol [Takahashi et al, 2004] wherefore the reciprocal of the concentration of plasma cortisol indicates the strength of D. Server 1 combines D and PC having a common integrator in Hypothalamus (H) into an integrated neuroendocrine unit of homeostasis termed Limbic system (L) by McLean, see figure 1. L serves as a Mammal freezing-for-emotional reset complex modifying the basal fight-or-flight response (RAS) by learning. As a self-sustaining system the 3-channel and 2-way upward impact of L is determined as the first derivative with respect to RAS: (S1) L = d(PC*D)/dRAS 3.1.3 Cognition (L3)Semantic memory recall in superior temporal sulcus (R)The Semantic Recollection (R) as associated with activity in the primary auditory cortex (Superior Temporal Sulcus, STS) is measured by theta-activity (Φ) in the EEG (in a range of 4-7 Hz) [Sauseng et al, 2006]. See, elaborated description at L4.Thalamo-cortico integrationThe characteristic resting pattern of the brain is α-waves in the 8-12 Hz/s band which indicates an autogenic cortical reset originated in Thalamus (α%) [Hanslmayr et al, 2007]. The dynamics of the associative cortices arising from PC is characterized by a polarization in between affective emotions (Rostral ACC), cognitive information (Caudal ACC) and mismatch by the Posterior Cingulate. Eventual Neocortical integration (AHA-experiences) has two different patterns: Firstly, one type of AHA-experience is identified as related to increased activity in medial frontal areas associated with voluntary activity and in temporal areas associated with semantic processing as expected from cognitive control. Secondly, a spontaneous (unprepared) AHA-experience of similarity-associations involving PC is identified as characterized by increased occipital activity consistent with integration of mismatched perceptions. To facilitate thalamo-cortico integration (AHA-experiences) we might rely on either frontoparietal cognitive control manipulating M or spontaneous integration by α%. The relevant servers involving the executive level are specified in section L4.3.1.4 The Executive (L4)A series of fMRI-studies evidence a tripartite structure of the frontal cortex:Logical analysis by the dorsolateral prefrontal cortex (A)The dorsolateral prefrontal cortex (dlPFC) which is the most recent phylogenetic step of evolution is an analyst with R as an important server [Robertson et al, 2001]. The cognitive control is specified in accordance with the Working Memory Model [Baddeley, 2002]: dlPFC is the executive centre of the phonological loop (A)STS is centre of the phonological loop operating RThe intraparietal sulcus, which is involved in numerical calculation [Cantlon et al, 2006], represents the visuospatial sketchpad (I) serving the integration of new perceptions in the phonological loop by AHA-experiencesCerebellum serves R with buffer relations to M i.e. coordination of walking.Server 2 refers to a frontal-parietal-downward logico-matematico intelligence centred in dlPFC which serves to sequence semantic memories [Robertson et al, 2001]:(S2) RIA Utility centre in the orbitofrontal cortex (U)The orbitofrontal cortex (OFC) receives emotional information from both Striatum, L and neocortical centres in the D [Alcaro, 2007]. An internal control centre in the left lateral part of the OFC accomplishes the integration of emotion and cognition suppressing emotions for cognitive analysis [Beer et al, 2007]. Such gradient of the present level of valence is anticipated in the classical economic concept of ranked utility []. A special fMRI-study by non-verbal cartoon tasks does not involve the dlPFC [Völlm et al, 2006]. It demonstrates that the ventromedial PFC manipulates emotions voluntarily independent of L and RAS. Server 3 is a bottom-up emotional intelligence from L towards the OFC [Wallis, 2007]. This LU-function is localized as the active centres during dreaming when the RIA is sleeping [Muzur et al, 2002]:(S3) LUPower of concentration (CONC) in the ventromedial prefrontal cortex (vmPFC)The vmPFC is crucial for frontal integration minimizing prediction errors [Schultz 2006 and Oya et al 2005]. This is achieved by voluntary emotional control of LU for cognitive analysis by RIA as the core function of CONC [Beer et al, 2007].3.2 INTEGRATED RESULTS3.2.1 The over-all modelThe major finding is that four phylogenetic subdivisions of the brain (L1-4) interact as a whole across levels in decision making. The neuroeconomic decision making formula combines S2 and S3 in a bottom-up - frontoparietal-downward learning process minimizing the error between expected and realized utilities (Non-integrated mismatches are preserved in the occipital lobes for delayed integration): CONC := LU-RIA Figure 2 shows the flowchart constituting CONC. Variables are summarized in table 1. Specificity, sensitivity and predictive value of the model are validated below.3.2.2 SpecificityA prototype of neuroeconomic fMRI-studies is the Ultimatum Game where the buyer can reject an offer i.e. an amount of money. If the buyer rejects both players receive nothing. The Ultimatum Game is correlated with a simultaneous brain activity in dlPFC (RIA) and ACC/Is (LU) [Sanfey et al, 2003] or both the complexities constituting CONC. This is indicates economic choices (maximizing utility by rational analysis) as a prototype of neurobiological decision-making. In all, the state of decision-making integrates two specialized mental states: the specific state of logico-mathematico learning characterized by significant MRI-activity in RIA [Robertson et al, 2007] and the specific state of emotional learning or ‘emphathizing' characterized by significant MRI-activity in LU [Singer 2006 and Völlm et al 2007]; As an opposite to the state of decision making relaxation serves an autonomic mental resetting with α-waves in the EEG [18].3.2.3 SensitivityFunctions commonly involved in social decision-making as specified in a review [Sanfey, 2007] serve as a checklist of the sensitivity of the model, see figure 4. All functions identified by Sanfey are included in our model, too. Moreover, 1) Hippocampus relevant to social perception, 2) Intraparietal Sulcus serving calculation and 3) the occipital visual association centre serving a delayed integration of mismatches are explicitly specified in our model. Regarding economic preferences other game-studies i.e. Prisoners Dilemma (PD) where each of two players makes one of two choices: cooperate or defect. More variants of PD have identified responses in both Insula and Striatum (L2) giving evidence to a social dimension in human decision-making [Fehr and Camerer, 2007]. A review of the insights in social decision-making from game theory and neuroscience concludes that neural correlates are evidenced for social values as reputation, trust, equality and cooperation [Sanfey, 2007]. In all, the neoclassical dogma of economic man pursuing a ‘bounded rationality' [Simon, 1978] is enlarged with an active social dimension.3.2.4 Predictive valueThe balance of emotional signals (LU) and logical analysis (RIA) as determined by CONC (prediction function) is a balance between expected and realized utility. Besides factual information this balance depends on the general state of mind or mood as determined by D in L. The behavioural significance of the mood is well-known to economists as closely related to the general business cycle: optimism enhances business while pessimism is associated with recession. A probabilistic study of economic choices finds a human bias towards risk and uncertainty [Takahashi, 2007] indicating a pessimistic mood. This finding is explained by the negative character of L-arousal [Yeung and Sanfey, 2004] mobilizing fear to miss a reward which is responded by CONC arousing fear to make errors. So, the typical relationship between the limbic system and Neocortex is indicated as an unsteady balance based on mutual fear which in both circuits are aroused by Amygdala. However, a minority of mankind is risk takers (optimists) exploring new possibilities. The interaction between the majority of risk-averters and a minority of risk-taking entrepreneurs explains the economic growth related to industrialization. Yet, the typical pessimistic mood explains an evidenced bias favouring immediate instead of future rewards more than justified by rational discounting [Loewenstein et al, 2008]. A serious affective barrier against long term planning in the post-industrial societies facing ecological challenges!4 DISCUSSION OF PALEO-NEOCORTICO INTEGRATIONFor neuroscience the close interaction between paleo- (limbic) and neocortical levels by three different pathways for emotional, associative and mismatches, respectively, indicates an upgrade of the autonomic nervous system from a subcortical somatic automatism to a primary centre of consciousness in ACC (L). The recognition of L demands a revision of some clinical protocols in the borderline between pharmaceutical and therapeutical interventions. However, at this stage the focus is the possibilities to improve CONC improving the general mood:1. Better satisfaction of the social preferences in L improves social learning in general and work group productivity in particular. Specific, the evidenced efficacy of human relations management of work groups known as the Hawthorne-effect [Mayo, 1949] is explained by the model as reduction of the negative valence of L. Recently, this mechanism is rediscovered in healthcare as a domina
Interpretable and Comparative Textual Dataset Exploration Using Near-Identity Mention Relations
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