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Journal articles on the topic 'Biological Basis Of Behavior'

Author: Grafiati

Published: 4 June 2021

Last updated: 6 February 2022

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1

Zinchuk, M. S., A. B. Guekht, N. V. Gulyaeva, A. S. Avedisova, R. G. Akzhigitov, and M. N. Grishkina. "Biological basis of suicidal behavior." Zhurnal nevrologii i psikhiatrii im. S.S. Korsakova 116, no. 8 (2016): 94. http://dx.doi.org/10.17116/jnevro20161168194-101.

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2

Robson, Arthur J. "The Biological Basis of Economic Behavior." Journal of Economic Literature 39, no. 1 (March 1, 2001): 11–33. http://dx.doi.org/10.1257/jel.39.1.11.

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This paper first considers the implications of biological evolution for economic preferences. It analyzes why utility functions evolved, considers evidence that utility is both hedonic and adaptive, and suggests why such adaptation might have evolved. Time preference and attitudes to risk are treated—in particular, whether the former is exponential and the latter are selfish. Arguments for another form of interdependence—a concern with status—are treated. The paper then considers the evolution of rationality. One hypothesis examined is that human intelligence and longevity were forged by hunter-gatherer economies; another is that intelligence was spurred by competitive social interactions.

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3

Pandey, Ghanshyam N. "Biological basis of suicide and suicidal behavior." Bipolar Disorders 15, no. 5 (June 15, 2013): 524–41. http://dx.doi.org/10.1111/bdi.12089.

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4

Primrose, David A. "Biological basis of behaviour." British Journal of Psychiatry 160, no. 1 (January 1992): 129–30. http://dx.doi.org/10.1192/bjp.160.1.129b.

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5

Hart, Benjamin L. "Biological basis of the behavior of sick animals." Neuroscience & Biobehavioral Reviews 12, no. 2 (June 1988): 123–37. http://dx.doi.org/10.1016/s0149-7634(88)80004-6.

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6

Rösgen, Jörg, Bernard Montgomery Pettitt, and David Wayne Bolen. "Uncovering the Basis for Nonideal Behavior of Biological Molecules†." Biochemistry 43, no. 45 (November 2004): 14472–84. http://dx.doi.org/10.1021/bi048681o.

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7

Kristan, William B. "Neuronal basis of behavior." Current Biology 2, no. 12 (December 1992): 648. http://dx.doi.org/10.1016/0960-9822(92)90113-o.

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8

Cole, Sherwood O. "The Biological Basis of Homosexuality: A Christian Assessment." Journal of Psychology and Theology 23, no. 2 (June 1995): 89–100. http://dx.doi.org/10.1177/009164719502300202.

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Concurrent with an interest in the incidence and characterization of homosexuality has been an increased interest in the biological basis of such behavior. The present article reviews evidence in support of a biological basis of homosexuality in three interrelated categories—genetic evidence, the prenatal neurohormonal hypothesis, and neuroanatomical evidence. An attempt is made to not only review studies that are representative of experimental findings in each of these categories, but to critically assess the evidence in terms of experimental protocol. In an attempt to provide a Christian assessment of the biological evidence, three conclusions are drawn: (1) evidence for a biological basis of homosexuality is sufficient to warrant its acceptance; (2) the nature of the biological influence on homosexuality is predisposing not determining, thus providing the potential for change; and (3) acceptance of a biological basis of homosexuality in no manner changes the biblical condemnation or prohibition of such behavior. Finally, the need for the Christian church to reach out and minister to homosexual individuals is briefly discussed.

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9

Constantine, Godwin Roger. "The Biological Basis of Performativity of Identity - Linking Scientific Evidence to Social Theory." Journal of Ethnic and Cultural Studies 4, no. 2 (December 29, 2017): 88. http://dx.doi.org/10.29333/ejecs/82.

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Identity is the essence of performance and performance is the essence of identity. Without identity our performance does not assume any cultural significance. Our relative identity allows our performance to be located in the socio-cultural space. Our identity forms the foundation for the discursive significance of our performance. However, our identity is not unique, it is established by performing a pre-existing script. The biological basis of identity can be understood by applying learning theories and by analyzing how these leant behavior is embedded in our neuronal network in the brain and how these behavior patterns are controlled by psychological factors to result in the identity we observe. Recent developments in the fields of neuroscience and functional neuro imaging have enabled us to study objectively the process of neural mechanisms and map areas of brain that are involved in learning various behavior patterns. These neuronal networks and the neuro transmitters play a key role in memory and behavior of animals. Aby studying the particular pattern of behavior and the brain area that mediates that behavior it will be possible to determine neuronal networks that control core identity characteristics and that control other less important characteristics. With the emergence of studies in neuroplasticity the possibility of relearning behaviors through new neuronal pathways may open new avenues to treat conditions that affect identity. Understanding the biological basis of identity will lead to widening of research area and better understanding of the concept.

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10

Moore, Jim. "Human Nature: A Critical Reader; The Biological Basis of Human Behavior." American Anthropologist 100, no. 3 (September 1998): 802–4. http://dx.doi.org/10.1525/aa.1998.100.3.802.

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11

Bowman, Eric. "Biological basis of substance abuse." Neuropsychologia 34, no. 2 (February 1996): 159. http://dx.doi.org/10.1016/s0028-3932(96)90003-2.

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12

O'Connor, Thomas G. "Updating biological bases of social behavior." Journal of Child Psychology and Psychiatry 55, no. 9 (August 11, 2014): 957–58. http://dx.doi.org/10.1111/jcpp.12313.

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13

Jasinska, Anna J., and Nelson B. Freimer. "The complex genetic basis of simple behavior." Journal of Biology 8, no. 8 (2009): 71. http://dx.doi.org/10.1186/jbiol172.

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14

Takagi, Suguru, and Richard Benton. "Animal Behavior: A Neural Basis of Individuality." Current Biology 30, no. 12 (June 2020): R710—R712. http://dx.doi.org/10.1016/j.cub.2020.04.052.

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15

Zhang, Mo, and Hai Shen. "Biological Communication Dynamic Model Research." Applied Mechanics and Materials 556-562 (May 2014): 4975–78. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.4975.

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Biological communication behavior is in everywhere, all over the nature, biological system and human society. In simple terms, Swarm intelligence is emerging though information communication and collaboration among some dispersed and simple individuals. Inspired by biological communication behavior, aimed at understanding swarm system collective dynamics behavior, and from the point of system cybernetics, this paper study the relevant biological communication dynamic model, such as the symbiotic model, attractive-repulsive model, external effect model and the multi-population coevolution model and so on. Also introduce the rules of these models, which provide theoretical basis for designing intelligent swarm intelligent system.

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16

Ratcliffe, Matthew. "Folk Psychology and the Biological Basis of Intersubjectivity." Royal Institute of Philosophy Supplement 56 (March 2005): 211–33. http://dx.doi.org/10.1017/s1358246100008857.

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Recent philosophical discussions of intersubjectivity generally start by stating or assuming that our ability to understand and interact with others is enabled by a ‘folk psychology’ or ‘theory of mind’. Folk psychology is characterized as the ability to attribute intentional states, such as beliefs and desires, to others, in order to predict and explain their behaviour. Many authors claim that this ability is not merely one amongst many constituents of interpersonal understanding but an underlying core that enables social life. For example, Churchland states that folk psychology ‘embodies our baseline understanding’ of others (1996, p. 3). Currie and Sterelny similarly assert that ‘our basic grip on the social world depends on our being able to see our fellows as motivated by beliefs and desires we sometimes share and sometimes do not’ (2000, p. 143). And, as Frith and Happe put it, ‘this ability appears to be a prerequisite for normal social interaction: in everyday life we make sense of each other's behaviour by appeal to a belief-desire psychology’ (1999, p. 2).

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17

Ratcliffe, Matthew. "Folk Psychology and the Biological Basis of Intersubjectivity." Royal Institute of Philosophy Supplement 56 (December 2005): 18–19. http://dx.doi.org/10.1017/s1358246105056109.

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Recent philosophical discussions of intersubjectivity generally start by stating or assuming that our ability to understand and interact with others is enabled by a ‘folk psychology’ or ‘theory of mind’. Folk psychology is characterized as the ability to attribute intentional states, such as beliefs and desires, to others, in order to predict and explain their behaviour. Many authors claim that this ability is not merely one amongst many constituents of interpersonal understanding but an underlying core that enables social life. For example, Churchland states that folk psychology ‘embodies our baseline understanding’ of others (1996, p. 3). Currie and Sterelny similarly assert that ‘our basic grip on the social world depends on our being able to see our fellows as motivated by beliefs and desires we sometimes share and sometimes do not’ (2000, p. 143). And, as Frith and Happé put it, ‘this ability appears to be a prerequisite for normal social interaction: in everyday life we make sense of each other’s behaviour by appeal to a belief-desire psychology’ (1999, p. 2).

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18

Cashmore, A. R. "The Lucretian swerve: The biological basis of human behavior and the criminal justice system." Proceedings of the National Academy of Sciences 107, no. 10 (February 8, 2010): 4499–504. http://dx.doi.org/10.1073/pnas.0915161107.

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19

Qamar, Sayyad Zahid, Maaz Akhtar, and Tasneem Pervez. "Swelling Behavior of Soft and Biological Materials." Key Engineering Materials 656-657 (July 2015): 580–85. http://dx.doi.org/10.4028/www.scientific.net/kem.656-657.580.

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Injuries or other ailments can cause swelling of tissues in the body, or of ligaments and tendons surrounding the bones. Such inflammation can lead to discomfort, pain, or even serious illness. Knowledge of the biomechanics of soft tissues is essential for correct prognosis and diagnosis. This requires good modeling and simulation of soft skeletal tissues, which cannot be carried out without experimental material characterization. Behavior of organic tissues is quite similar to that of elastomeric materials that swell when immersed in certain fluids. This work investigates the effect of swelling on compression and bulk properties and the polymeric structure of a water-based elastomer. A drastic change in mechanical and structural properties is observed during the initial swelling period. Elastic and shear moduli decrease by nearly 90% within a few days, and then exhibit almost no change. An opposite trend can be observed for Poisson’s ratio; dramatic increase in the beginning, then a near-constant behavior. Variation in bulk modulus is somewhat fluctuating, but the general trend is a decrease due to swelling. After ten days of swelling, value of Poisson’s ratio becomes approximately 0.5. A sharp decrease in the first week of swelling can be observed in chain density, while cross-link average molecular weight shows the opposite trend of an increase with swelling (with minor fluctuations). Results of this study can provide the material input values for modeling and simulation of the behavior of tissues and other soft biological materials. This, in turn, can form a basis for more detailed analytical and computational studies in biomechanics and biomedical engineering.

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20

Lanfranchi, Angela. "A Scientific Basis for Humanae Vitae and Natural Law." Linacre Quarterly 85, no. 2 (April 12, 2018): 148–54. http://dx.doi.org/10.1177/0024363918756191.

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This article will review Humanae Vitae’s predictions of the effect of oral contraceptives (the pill) on male–female relationships and societal behaviors. A scientific, biochemical basis underpinning these predictions is made. Evidence of human pheromones will be given. Evidence for the changes in male and female pheromones caused by the pill is given. Observational and experimental evidence of changes in primate and human behaviors by pheromones is detailed. The role these changes have caused in attractiveness and selection of mate by both males and females in preferences concerning major histocompatibility genes is examined. These changes have also resulted in societal changes in sexual behavior and family structure and have led to increased violence against women. Biochemical evidence for the abortifacient properties of the pill is given. The use of natural family planning is given as a needed alternative to the harms of the pill. Summary: The human biological bases of Humanae Vitae’s predictions of the effect of the pill on male–female relationships are examined. Evidence of the presence of pheromones in primates and humans is given. The pill changes human pheromones, odors which are subconsciously detected. These pheromones cause humans to change what they find attractive in a mate. Choosing a mate while on the pill can result in unstable and more violent unions. The biological basis for the fact that the pill causes abortion of human embryos is given. A healthy alternative for fertility control is explained.

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21

Bozorgmehr, Ali, Mohammad Ghadirivasfi, Mostafa Tavakoli, Hamid Rahmani, Fahimeh Heydari, and Esmaeil Shahsavand Ananloo. "Integrated analysis of the genetic basis of suicidal behavior." Psychiatric Genetics 28, no. 2 (April 2018): 31–37. http://dx.doi.org/10.1097/ypg.0000000000000191.

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22

Eap, Dana, Sara Correa, Hanh Ngo-Vu, and Charles D. Derby. "Chemosensory Basis of Feeding Behavior in Pacific White Shrimp, Litopenaeus vannamei." Biological Bulletin 239, no. 2 (October 1, 2020): 115–31. http://dx.doi.org/10.1086/710337.

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23

Courtet, P. "Clinical Use of Biomarkers in Suicidal Behaviors." European Psychiatry 41, S1 (April 2017): S41. http://dx.doi.org/10.1016/j.eurpsy.2017.01.184.

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The epidemiology, risk factors, and biological basis of suicidal behaviors have been the object of an ever–increasing research in the last three decades. During this period, researchers all over the world have identified potential biomarkers of risk and developed several theories about the mechanisms leading to suicidal behavior. However, the lack of common terminology, instruments, and cooperation has been a major deterrent. Today, the community has established the bases for this collaboration and evidence coming from neuroscientific studies can already be applied to the field of suicidology. We present here a potential semiology based on current evidence coming from biological, clinical, and neuroimaging studies.Disclosure of interestThe author declares that he has no competing interest.

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24

Numan, M. "Neural basis of maternal behavior in the rat." Psychoneuroendocrinology 13, no. 1-2 (1988): 47–62. http://dx.doi.org/10.1016/0306-4530(88)90006-6.

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25

CROCI, SOLÈNE, ALAIN BUTET, and PHILIPPE CLERGEAU. "DOES URBANIZATION FILTER BIRDS ON THE BASIS OF THEIR BIOLOGICAL TRAITS?" Condor 110, no. 2 (May 2008): 223–40. http://dx.doi.org/10.1525/cond.2008.8409.

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26

Hoehl, Stefanie, Vincent M. Reid, and Eugenio Parise. "The Biological Basis of Social Cognition During Development." Neuropsychologia 126 (March 2019): 1–2. http://dx.doi.org/10.1016/j.neuropsychologia.2019.02.020.

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27

Bewers, J. M., J. M. Osborne, D. H. Loring, and M. Porebski. "A Geochemical and Biological Basis for Marine Sediment Quality Guidelines." Chemistry and Ecology 14, no. 3-4 (December 1998): 173–96. http://dx.doi.org/10.1080/02757549808037602.

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28

Svetina, Sa?a, and Bo?tjan ?ek? "Shape behavior of lipid vesicles as the basis of some cellular processes." Anatomical Record 268, no. 3 (October 15, 2002): 215–25. http://dx.doi.org/10.1002/ar.10156.

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29

Chase, Thomas E., and Robert C. Ullrich. "Genetic Basis of Biological Species in Heterobasidion annosum: Mendelian Determinants." Mycologia 82, no. 1 (January 1990): 67. http://dx.doi.org/10.2307/3759964.

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30

Chase, Thomas E., and Robert C. Ullrich. "Genetic Basis of Biological Species in Heterobasidion Annosum: Mendelian Determinants." Mycologia 82, no. 1 (January 1990): 67–72. http://dx.doi.org/10.1080/00275514.1990.12025842.

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31

Gilbertson-White, Stephanie, Bradley E. Aouizerat, and Christine Miaskowski. "Methodologic Issues in the Measurement of Cytokines to Elucidate the Biological Basis for Cancer Symptoms." Biological Research For Nursing 13, no. 1 (August 26, 2010): 15–24. http://dx.doi.org/10.1177/1099800410379497.

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Multiple concurrent symptoms are highly prevalent in patients with cancer. However, little is known about the relationships among these symptoms and their underlying mechanisms. A number of cytokines that are involved in the development of sickness behavior are hypothesized to be a mechanism for symptom clusters. Measurement of these cytokines would provide valuable information that could be used to elucidate mechanisms underlying the development of symptom clusters and the identification of potential targets for intervention studies. In this article, the authors explore several issues that warrant careful consideration when designing a research study involving the use of a cytokine as a biomarker in symptom cluster research. These issues include which molecules to measure, which specimens to collect, the timing of specimen collection and processing, and which technologies to use to measure the biomarker and the sensitivity and specificity of the assay system. The article begins with a brief discussion of cytokines and sickness behavior and the role of the cytokines in cancer-related symptoms.

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32

Wagner, G. P. "The Origin of Morphological Characters and the Biological Basis of Homology." Evolution 43, no. 6 (September 1989): 1157. http://dx.doi.org/10.2307/2409354.

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33

Wagner, G. P. "THE ORIGIN OF MORPHOLOGICAL CHARACTERS AND THE BIOLOGICAL BASIS OF HOMOLOGY." Evolution 43, no. 6 (September 1989): 1157–71. http://dx.doi.org/10.1111/j.1558-5646.1989.tb02566.x.

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34

Raghu, S., and Rieks D. van Klinken. "Refining the ecological basis for agent selection in weed biological control." Australian Journal of Entomology 45, no. 4 (November 2006): 251–52. http://dx.doi.org/10.1111/j.1440-6055.2006.00546.x.

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35

Hart, Benjamin L., Lynette A. Hart, Michael S. Mooring, and Reardon Olubayo. "Biological basis of grooming behaviour in antelope: the body-size, vigilance and habitat principles." Animal Behaviour 44, no. 4 (October 1992): 615–31. http://dx.doi.org/10.1016/s0003-3472(05)80290-8.

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36

MOORING, MICHAEL S., and W. M. SAMUEL. "The biological basis of grooming in moose: programmed versus stimulus-driven grooming." Animal Behaviour 56, no. 6 (December 1998): 1561–70. http://dx.doi.org/10.1006/anbe.1998.0915.

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37

Zea, Luis, Nripesh Prasad, Shawn E. Levy, Louis Stodieck, Angela Jones, Shristi Shrestha, and David Klaus. "A Molecular Genetic Basis Explaining Altered Bacterial Behavior in Space." PLOS ONE 11, no. 11 (November 2, 2016): e0164359. http://dx.doi.org/10.1371/journal.pone.0164359.

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38

Ware, D. M., and R. W. Tanasichuk. "Biological Basis of Maturation and Spawning Waves in Pacific Herring (Clupea harengus pallasi)." Canadian Journal of Fisheries and Aquatic Sciences 46, no. 10 (October 1, 1989): 1776–84. http://dx.doi.org/10.1139/f89-225.

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Maturation rates (measured as the change in the gonosomatic index (GSI) with time) over the last month of the annual maturation cycle were estimated for male and female herring in British Columbia, between 1982–87. The data were analyzed to determine interannual and interregional differences in the maturation rate and its influence on spawning time. The data also indicated that in some areas herring spawned in discrete waves — the largest fish tended to spawn first and the smaller fish in subsequent waves. Each spawning wave lasted about 5–6 d and the interwave interval varied from 8–26 d in the Strait of Georgia. General equations were developed to describe gonadal growth over the entire maturation cycle. These equations accounted for the observed differences in: (1) the maturation rates between the sexes (males initially mature faster), (2) the interregional and interannual variation in the timing of spawning (herring tend to spawn later at higher latitudes, and earlier than normal when its warmer), and (3) provide an explanation for spawning waves. All of these phenomena derive from the fact that the instantaneous rate at which the gonad grows during the maturation cycle in both sexes depends on the weight of the fish, and the daily sea temperature.

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39

Ramy, H. "The Biology of Cognitive Behavior Therapy." European Psychiatry 41, S1 (April 2017): S637. http://dx.doi.org/10.1016/j.eurpsy.2017.01.1047.

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Cognitive behavior therapy outcomes and the mechanism of change that are related to its effects have traditionally been investigated on the psychological abilities, personalities or social functioning. Many psychiatrists have also held the unfortunate dichotomized position that psychotherapy is a treatment for “psychologically based” disorders, while medication is for “biologically based” disorders. During the past several decades, it has become clear that all mental processes drive from mechanisms of the brain. This means that any change in our psychologically processes is reflected by changes in the functions or structures of the brain. Straightforward reductionist stances, however, are unfounded because there is clear evidence that our subjective experiences affect the brain. Plastic changes in the brain have been difficult to study in humans, but there has been more than one successful trial. Changes in the brain in relation to experience have been detected at the cellular and molecular level using different experimental approaches. The advent of functional neuro-imaging, including photon emission CT (SPECT), positron emission topography, and functional MRI, has made it possible to study changes at the brain systems level (by measuring changes in the brain blood flow or metabolism) associated with cognitive behavior changes. The presentation will shed light on the biological basis of CBT reviewing the evidence from a historical perspective. In addition the imaging studies will be reviewed with emphasis on future perspectives in the use of CBT in the treatment of various psychiatric disorders and the importance of clarifying the biological changes associated with improvement.Disclosure of interestThe authors have not supplied their declaration of competing interest.

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40

Courtet, P. "A neurosciences based – semiology of suicidal behavior." European Psychiatry 33, S1 (March 2016): S49. http://dx.doi.org/10.1016/j.eurpsy.2016.01.915.

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The epidemiology, risk factors and biological basis of suicidal behaviors have been the object of an ever-increasing research in the last three decades. During this period, researchers all over the world have identified potential biomarkers of risk and developed several theories about the mechanisms leading to suicidal behavior. However, the lack of common terminology, instruments and cooperation has been a major deterrent. Today, the community has established the bases for this collaboration and evidence coming from neuroscientific studies can already be applied to the field of suicidology. We present here a potential semiology based on current evidence coming from biological, clinical and neuroimaging studies. Besides suicidal ideation and warning signs, the clinical features related to suicide risk and revealed by neuroscientific studies include notably: impulsive-aggression and hopelessness as well as high web consumption, sedentary behaviors and reduced sleep time, an enhanced sensibility to social exclusion and loneliness, a decreased sensitivity to detect social support, interpersonal problems related to decision-making impairments, difficulties to regulate negative emotional states, a propensity to perceive psychic and also physical pain and to receive opiates treatments. Improving the assessment will also open new targets for suicide prevention. In the short-term, some of these targets await us: standard protocols for evaluation of risk, healthcare continuity, implication of the family/caregivers, mitigation of social or psychological pain.Disclosure of interestThe author has not supplied his declaration of competing interest.

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41

Crews, Douglas E. "A Means to an End: The Biological Basis of Aging and Death (review)." Human Biology 73, no. 6 (2001): 897–901. http://dx.doi.org/10.1353/hub.2001.0078.

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42

Jeibmann, Astrid, Martin Hasselblatt, Stefan Pfister, Ronald Sträter, Angela Brentrup, Markus Holling, Thomas Niederstadt, Werner Paulus, and Michael C. Frühwald. "From glioblastoma to gangliocytoma: an unforeseen but welcome shift in biological behavior." Journal of Neurosurgery: Pediatrics 4, no. 5 (November 2009): 475–78. http://dx.doi.org/10.3171/2009.6.peds097.

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The prognosis in children harboring a glioblastoma multiforme (GBM) is usually poor. Few GBMs in children, however, seem to respond quite well to adjuvant chemotherapy. The biological basis for such chemotherapy sensitivity remains uncertain. In this paper the authors report the case of a 2-month-old girl with a histologically confirmed GBM (WHO Grade IV) in whom chemotherapy was accompanied by differentiation of the malignant primary tumor into a typical gangliocytoma (WHO Grade I) showing ganglioid differentiation and expression of neuronal markers synaptophysin, neurofilament, and NeuN as well as a low Ki 67/MIB-1 proliferation index. Array-comparative genomic hybridization did not reveal genetic alterations in either specimen. Even though the underlying biological mechanisms remain to be elucidated, closer examination of frequency and prognostic significance of neuronal differentiation in pediatric GBMs within ongoing and future clinical trials may be warranted.

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43

Lin, Suewei, Bhagyashree Senapati, and Chang-Hui Tsao. "Neural basis of hunger-driven behaviour in Drosophila." Open Biology 9, no. 3 (March 2019): 180259. http://dx.doi.org/10.1098/rsob.180259.

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Hunger is a motivational state that drives eating and food-seeking behaviour. In a psychological sense, hunger sets the goal that guides an animal in the pursuit of food. The biological basis underlying this purposive, goal-directed nature of hunger has been under intense investigation. With its rich behavioural repertoire and genetically tractable nervous system, the fruit fly Drosophila melanogaster has emerged as an excellent model system for studying the neural basis of hunger and hunger-driven behaviour. Here, we review our current understanding of how hunger is sensed, encoded and translated into foraging and feeding behaviours in the fruit fly.

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44

KIM, SEUNGCHAN, HUAI LI, EDWARD R. DOUGHERTY, NANWEI CAO, YIDONG CHEN, MICHAEL BITTNER, and EDWARD B. SUH. "CAN MARKOV CHAIN MODELS MIMIC BIOLOGICAL REGULATION?" Journal of Biological Systems 10, no. 04 (December 2002): 337–57. http://dx.doi.org/10.1142/s0218339002000676.

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A fundamental question in biology is whether the network of interactions that regulate gene expression can be modeled by existing mathematical techniques. Studies of the ability to predict a gene's state based on the states of other genes suggest that it may be possible to abstract sufficient information to build models of the system that retain steady-state behavioral characteristics of the real system. This study tests this possibility by: (i) constructing a finite state homogeneous Markov chain model using a small set of interesting genes; (ii) estimating the model parameters based on the observed experimental data; (iii) exploring the dynamics of this small genetic regulatory network by analyzing its steady-state (long-run) behavior and comparing the resulting model behavior to the observed behavior of the original system. The data used in this study are from a survey of melanoma where predictive relationships (coefficient of determination, CoD) between 587 genes from 31 samples were examined. Ten genes with strong interactive connectivity were chosen to formulate a finite state Markov chain on the basis of their role as drivers in the acquisition of an invasive phenotype in melanoma cells. Simulations with different perturbation probabilities and different iteration times were run. Following convergence of the chain to steady-state behavior, millions of samples of the results of further transitions were collected to estimate the steady-state distribution of network. In these samples, only a limited number of states possessed significant probability of occurrence. This behavior is nicely congruent with biological behavior, as cells appear to occupy only a negligible portion of the state space available to them. The model produced both some of the exact state vectors observed in the data, and also a number of state vectors that were near neighbors of the state vectors from the original data. By combining these similar states, a good representation of the observed states in the original data could be achieved. From this study, we find that, in this limited context, Markov chain simulation emulates well the dynamic behavior of a small regulatory network.

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45

Cox, Donald. "Biological Basics and the Economics of the Family." Journal of Economic Perspectives 21, no. 2 (April 1, 2007): 91–108. http://dx.doi.org/10.1257/jep.21.2.91.

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Many economic models of the family are based on a generic “person 1—person 2” household or “parent—child” family, rather than their anatomically correct counterparts: sons and daughters, fathers and mothers, and grandfathers and grandmothers. These economic models can offer powerful insights into family behavior, but also can leave certain patterns unexplained and neglect potentially important crosscurrents. “Bio-founded” approaches explicitly consider sex differences in reproductive capabilities and constraints, and can illuminate differences in the goals and interests of men versus women regarding preferences for a mate, decisions to marry or to terminate a marriage, how much to invest in a relationship, how much to invest in children, and how much to value the quality relative to the quantity of children Melding biological insights with family economics can cast new light on existing knowledge and open up novel paths for research. This paper generates biologically based hypotheses about family behavior by using Hamilton's rule, which holds that the costs and benefits of altruistic acts are weighted by the closeness of the genetic relationship, and by noting various fundamentals of human reproductive biology (for instance, a father might be uncertain of his genetic relationship to offspring, but a mother almost never is). This strategy generates a unified approach for modeling diverse aspects of family behavior. My discussion of biological fundamentals will include applications, empirical illustrations, and suggestions for how to merge these basics with current economic thinking.

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Marušić-Jablanović, Milica, and Jelena Stanišić. "Prediction of environmental activism: The role of knowledge, attitudes, affects and behaviors." Andragoske studije, no. 2 (2020): 127–44. http://dx.doi.org/10.5937/andstud2002127m.

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The components of ecological li teracy comprise knowledge, attitudes, affect, behavior, and environmental activism. The goal of this paper is to establish whether environmental activism can be predicted on the basis of environmental knowledge, proenvironmental attitudes, affect, and behavior. In addition to this, the goal of the research is to examine to what extent individuals of different activism levels differ in terms of knowledge of basic environmental problems, expression of the attitude of ecological apathy, anthropocentrism, belonging to nature and connection with nature, as well as usual practices of pro-environmental behavior. By surveying a sample of adult respondents from Serbia who belong to a group devoted to an environmental problem (N=255), we have discovered that general environmental knowledge alone does not contribute to pro-environmental behaviors or environmental activism. The predictors of activism are pro-environmental attitudes, an affective attitude towards nature, and common pro-environmental behaviors, even though they help distinguish a group of barely active members from two groups of more active members, but they do not help distinguish those who are active in a virtual space from those who participate personally. The groups are further distinguished by other variables, such as the locus of control, values, and the phenomenon of quasi-activism. The established connection between knowledge and emotional affinity towards nature seems to represent a reciprocal relationship, and indicates that the right way to learn is to acquire knowledge, but while developing a love for nature.

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Kim, Nancy S., Woo-kyoung Ahn, Samuel G. B. Johnson, and Joshua Knobe. "The influence of framing on clinicians’ judgments of the biological basis of behaviors." Journal of Experimental Psychology: Applied 22, no. 1 (March 2016): 39–47. http://dx.doi.org/10.1037/xap0000070.

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Moore, Dani, C. Tate Holbrook, Melissa G. Meadows, and Lisa A. Taylor. "The Mating Game: A Classroom Activity for Undergraduates That Explores the Evolutionary Basis of Sex Roles." American Biology Teacher 74, no. 9 (November 1, 2012): 648–51. http://dx.doi.org/10.1525/abt.2012.74.9.9.

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In species that reproduce sexually, an individual’s fitness depends on its ability to secure a mate (or mates). Although both males and females are selected to maximize their reproductive output, the mating strategies of the two sexes can differ dramatically. We present a classroom simulation that allows undergraduates to actively experience how differences in parental investment lead to differences in reproductive behavior. Students will understand why males generally compete for mates whereas females generally choose among mates. The activity provides a foundation for exploring advanced topics in animal behavior, or it can be adapted for introductory biology courses.

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Broderick, Patricia A. "Cocaine: On-line analysis of an accumbens amine neural basis for psychomotor behavior." Pharmacology Biochemistry and Behavior 40, no. 4 (December 1991): 959–68. http://dx.doi.org/10.1016/0091-3057(91)90112-f.

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Buha, Natasa, Milica Gligorovic, and Jasmina Maksic. "Challenging behavior: Behavioral phenotypes of some genetic syndromes." Srpski arhiv za celokupno lekarstvo 142, no. 9-10 (2014): 621–27. http://dx.doi.org/10.2298/sarh1410621b.

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Challenging behavior in individuals with mental retardation (MR) is relatively frequent, and represents a significant obstacle to adaptive skills. The frequency of specific forms and manifestations of challenging behavior can depend on a variety of personal and environmental factors. There are several prominent theoretical models regarding the etiology of challenging behavior and psychopathology in persons with MR: behavioral, developmental, socio-cultural and biological. The biological model emphasizes the physiological, biochemical and genetic factors as the potential source of challenging behavior. The progress in the field of genetics and neuroscience has opened the opportunity to study and discover the neurobiological basis of phenotypic characteristics. Genetic syndromes associated with MR can be followed by a specific set of problems and disorders which constitutes their behavioral phenotype. The aim of this paper was to present challenging behaviors that manifest in the most frequently studied syndromes: Down syndrome, Fragile X syndrome, Williams syndrome, Prader-Willi syndrome and Angelman syndrome. The concept of behavioral phenotype implies a higher probability of manifesting specific developmental characteristics and specific behaviors in individuals with a certain genetic syndrome. Although the specific set of (possible) problems and disorders is distinctive for the described genetic syndromes, the connection between genetics and behavior should be viewed through probabilistic dimension. The probabilistic concept takes into consideration the possibility of intra-syndrome variability in the occurrence, intensity and time onset of behavioral characteristics, at which the higher variability the lower is the specificity of the genetic syndrome. Identifying the specific pattern of behavior can be most important for the process of early diagnosis and prognosis. In addition, having knowledge about behavioral phenotype can be a landmark in the creation of targeted treatment strategies for individuals with a specific genetic syndrome.

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