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Filozofia kognitywistyki

Informacje ogólne

Kod przedmiotu: 2401-K-S2-1-FK
Kod Erasmus / ISCED: (brak danych) / (0228) Interdyscyplinarne programy i kwalifikacje związane z naukami humanistycznymi Kod ISCED - Międzynarodowa Standardowa Klasyfikacja Kształcenia (International Standard Classification of Education) została opracowana przez UNESCO.
Nazwa przedmiotu: Filozofia kognitywistyki
Jednostka: Katedra Kognitywistyki
Grupy: Kognitywistyka - s2 - 1 rok
Punkty ECTS i inne: 4.00 Podstawowe informacje o zasadach przyporządkowania punktów ECTS:
  • roczny wymiar godzinowy nakładu pracy studenta konieczny do osiągnięcia zakładanych efektów uczenia się dla danego etapu studiów wynosi 1500-1800 h, co odpowiada 60 ECTS;
  • tygodniowy wymiar godzinowy nakładu pracy studenta wynosi 45 h;
  • 1 punkt ECTS odpowiada 25-30 godzinom pracy studenta potrzebnej do osiągnięcia zakładanych efektów uczenia się;
  • tygodniowy nakład pracy studenta konieczny do osiągnięcia zakładanych efektów uczenia się pozwala uzyskać 1,5 ECTS;
  • nakład pracy potrzebny do zaliczenia przedmiotu, któremu przypisano 3 ECTS, stanowi 10% semestralnego obciążenia studenta.
Język prowadzenia: polski

Zajęcia w cyklu "Semestr zimowy 2021/22" (zakończony)

Okres: 2021-10-01 - 2022-02-20
Wybrany podział planu:
Przejdź do planu
Typ zajęć:
Konwersatorium, 30 godzin więcej informacji
Koordynatorzy: Przemysław Nowakowski
Prowadzący grup: Przemysław Nowakowski
Lista studentów: (nie masz dostępu)
Zaliczenie: Przedmiot - Zaliczenie na ocenę
Konwersatorium - Zaliczenie na ocenę
Skrócony opis:

Na zajęciach zajmiemy się podstawowymi zagadnieniami filozofii kognitywistyki, uprawianej w kontekście historycznego i praktycznego zwrotu w filozofii nauki. Omówimy zarówno historię rozwoju dyscypliny, jak i jej bieżące problemy.

Pełny opis:

Filozofia kognitywistyki, to wyróżniony przedmiotowo dział filozofii nauki. Na zajęciach będziemy przyglądać się z perspektywy historii i filozofii nauki takim kwestiom jak przedmiot badań kognitywistycznych (numery spotkań: 3,4,5); obecnym w kognitywistyce koncepcjom/rodzajom wyjaśniania (7,8); kontrowersjom wokół zintegrowania kognitywistyki (6,14). Ponadto przyjrzymy się filozoficznym badaniom nad eksperymentami, metodami & technikami, danymi czy rolą teorii w kognitywistyce (9,10,11,12), a także jej podstawowymi pojęciami (13).

Celem zajęć jest nie tylko zapoznanie uczestników z klasycznymi i aktualnymi problemami filozofii kognitywistyki, ale także, a może przede wszystkim, rozwinięcie właściwej dla filozofii nauki wrażliwości na filozoficzny wymiar problemów z jakimi mierzą się w swojej codziennej praktyce badawcze, tu: kognitywiści.

Literatura:

1_Zajęcia_wprowadzające

2_Historia_i_rozwój_kognitywistyki

Literatura:

Bechtel, W., Abrahamsen, A., & Graham, G. (2017). The life of cognitive science. W: Bechtel, W., Graham, G., & Balota, D. A. (red.). A companion to cognitive science Oxford: Blackwell. s.1-104.

Cohen-Cole, J. (2007). Instituting the science of mind: intellectual economies and disciplinary exchange at Harvard's Center for Cognitive Studies. The British Journal for the History of Science, 40(4), s.567-597.

Crowther‐Heyck, H. (2006). Herbert Simon and the GSIA: Building an interdisciplinary community. Journal of the History of the Behavioral Sciences, 42(4), s.311-334.

Literatura dodatkowa:

Gardner, H. (1987). The mind's new science: A history of the cognitive revolution. Basic books.

Graff, Harvey J. 2015. Undisciplining Knowledge: Interdisciplinarity in the Twentieth Century. Baltimore: Johns Hopkins University Press.

3_Czym_jest_poznanie?

Literatura:

Aizawa, K. (2017). Cognition and behavior. Synthese 194, 4269–4288.

Akagi, M. (2018). Rethinking the problem of cognition. Synthese 195, 3547–3570.

Allen, C. (2017). On (not) defining cognition. Synthese 194, 4233–4249.

Keijzer, F. (2021). Demarcating cognition: the cognitive life sciences. Synthese 198, 137–157.

Literatura dodatkowa:

Baum, C. (2016). Stabilizing Cognition: An STS Approach to the Sloan Foundation Report. Theory & Psychology, 26(6), 773-787.

Buckner, C., Fridland, E. (2017) What is cognition? angsty monism, permissive pluralism(s), and the future of cognitive science. Synthese 194, 4191–4195.

Buckner, C. (2015). A property cluster theory of cognition. Philosophical Psychology, 28(3), 307–336.

4_Przedmiot_badań_kognitywistycznych

Literatura:

Bogen, J., & Woodward, J. (1988). Saving the phenomena. The Philosophical Review, 97(3), 303-352.

Cummins, R. (2000). “How does it work?” vs. “What are the laws?” Two conceptions of psychological explanation. w: Keil, F., Wilson, R. (Eds.), Explanation and cognition. MIT Press, s.117-145.

Feest, U. (2017). Phenomena and objects of research in the cognitive and behavioral sciences. Philosophy of Science, 84(5), 1165-1176.

Literatura dodatkowa:

Danziger, K. (2003). Where history, theory, and philosophy meet: The biography of psychological objects. About psychology: Essays at the crossroads of history, theory, and philosophy, 19-33.

Nowakowski, P. R. (2019). Epistemic Challenges: Engaging Philosophically in Cognitive Science. Ruch Filozoficzny, 75(2).

Rheinberger H.­J. (2015). Epistemologia historyczna. tłum. Jan Surman, Warszawa: Oficyna Naukowa.

5_Rodzaje_naturalne_w kognitywistyce

Literatura:

Fedorenko, E., Blank, I. A. (2020). Broca’s area is not a natural kind. Trends in cognitive sciences, 24(4), 270-284.

Gomez-Lavin, J. (2021). Working memory is not a natural kind and cannot explain central cognition. Review of Philosophy and Psychology, 12(2), 199-225.

Taylor, H. (2018). Attention, psychology, and pluralism. The British Journal for the Philosophy of Science, 69(4), 935-956.

Barrett, L. F. (2006). Are emotions natural kinds?. Perspectives on psychological science, 1(1), 28-58.

Literatura dodatkowa:

Bird, Alexander and Emma Tobin, "Natural Kinds", The Stanford Encyclopedia of Philosophy (Spring 2018 Edition), Edward N. Zalta (ed.), URL = <https://plato.stanford.edu/archives/spr2018/entries/natural-kinds/>.

Boyd, R. (2013). Kinds as the “workmanship of men”: Realism, constructivism, and natural kinds. W: Rationalität, Realismus, Revision/Rationality, Realism, Revision, (red.) Nida-Rümelin, J. de Gruyter, s. 52-89.

Cheng, S., & Werning, M. (2016). What is episodic memory if it is a natural kind?. Synthese, 193(5), 1345-1385.

Hommel, B., Chapman, C. S., Cisek, P., Neyedli, H. F., Song, J. H., & Welsh, T. N. (2019). No one knows what attention is. Attention, Perception, & Psychophysics, 81(7), 2288-2303.

Keijzer, F. (2019). Is ‘the brain’a helpful metaphor for neuroscience?. Behavioral and Brain Sciences, 42, e234.

Michaelian, K. (2011). Is memory a natural kind?. Memory Studies, 4(2), 170-189.

Weidman, A. C., Steckler, C. M., & Tracy, J. L. (2017). The jingle and jangle of emotion assessment: Imprecise measurement, casual scale usage, and conceptual fuzziness in emotion research. Emotion, 17(2), 267.

6_Pluralizm a unifikacja w kognitywistyce

Litaratura:

Dale, R. (2008). The possibility of a pluralist cognitive science. Journal of Experimental and Theoretical Artificial Intelligence, 20(3), 155-179.

Miłkowski, M. (2016). Unification strategies in cognitive science. Studies in Logic, Grammar and Rhetoric, 48(1), 13-33.

Literatura dodatkowa:

Dale, R., Dietrich, E., & Chemero, A. (2009). Explanatory pluralism in cognitive science. Cognitive science, 33(5), 739-742.

Fodor, J. (1974/2008) Nauki szczegółowe (albo: niejednorodność nauk jako hipoteza robocza), tłum. Marcin Gokieli, w: Miłkowski, M., Poczobut, R. (red.). Analityczna metafizyka umysłu, Wydawnictwo IFiS PAN, Warszawa, s. 56-75.

Miłkowski, M., & Nowakowski, P. (2019). Representational unification in cognitive science: Is embodied cognition a unifying perspective?. Synthese, 1-22.

Potochnik, A., & Sanches de Oliveira, G. (2020). Patterns in cognitive phenomena and pluralism of explanatory styles. Topics in cognitive science, 12(4), 1306-1320.

7_Wyjaśnianie_w_kognitywistyce_1

Literatura:

Franks, B. (1995). On explanation in the cognitive sciences: Competence, idealization, and the failure of the classical cascade. The British journal for the philosophy of science, 46(4), 475-502.

Marraffa, M., & Paternoster, A. (2013). Functions, levels, and mechanisms: Explanation in cognitive science and its problems. Theory & Psychology, 23(1), 22-45.

Piccinini, G., & Craver, C. (2011). Integrating psychology and neuroscience: Functional analyses as mechanism sketches. Synthese, 183(3), 283-311.

Literatura dodatkowa:

Bechtel, W., & Shagrir, O. (2015). The non‐redundant contributions of Marr's three levels of analysis for explaining information‐processing mechanisms. Topics in Cognitive Science, 7(2), 312-322.

Shagrir, O. (2010). Marr on computational-level theories. Philosophy of science, 77(4), 477-500.

8_Wyjaśnianie_kognitywistyce_2

Literatura:

Bertolero, M. A., & Bassett, D. S. (2020). On the nature of explanations offered by network science: A perspective from and for practicing neuroscientists. Topics in Cognitive Science, 12(4), 1272-1293.

Stepp, N., Chemero, A. and Turvey, M.T. (2011), Philosophy for the Rest of Cognitive Science. Topics in Cognitive Science, 3: 425-437.

Literatura dodatkowa:

Craver, C. F. (2016). The explanatory power of network models. Philosophy of Science, 83(5), 698-709.

Faskowitz, J., Betzel, R. F., & Sporns, O. (2021). Edges in brain networks: Contributions to models of structure and function. Network Neuroscience. Advance publication. https://doi.org/10.1162/netn_a_00204

Zednik, C. (2011). The nature of dynamical explanation. Philosophy of Science, 78(2), 238-263.

9_Filozofia_eksperymentu_w_kognitywistyce_a_różne_metody/techniki_badawcze

Literatura:

Bechtel, W. (2002). Aligning multiple research techniques in cognitive neuroscience: Why is it important?. Philosophy of Science, 69(S3), S48-S58.

Bickle, J. (2018). From microscopes to optogenetics: Ian Hacking vindicated. Philosophy of Science, 85(5), 1065-1077.

Sullivan, J. A. (2009). The multiplicity of experimental protocols: a challenge to reductionist and non-reductionist models of the unity of neuroscience. Synthese, 167(3), 511-539.

Literatura dodatkowa:

Bechtel, William (2000), “From Imaging to Believing: Epistemic Issues in Generating Bio- logical Data”, w: R. Creath and J. Maienschein (red.), Biology and Epistemology. Cam- bridge: Cambridge University Press, s.138–163.

Hanson, S. J. E., & Bunzl, M. E. (2010). Foundational issues in human brain mapping. MIT Press.

Ritchie, J. B., Kaplan, D. M., & Klein, C. (2019). Decoding the brain: Neural representation and the limits of multivariate pattern analysis in cognitive neuroscience. The British journal for the philosophy of science, 70(2), 581-607.

Stufflebeam, R. S., & Bechtel, W. (1997). PET: Exploring the Myth and the Method. Philosophy of Science, 64, S95-S106.

Sullivan, J. A. (2018). Optogenetics, pluralism, and progress. Philosophy of Science, 85(5), 1090-1101.

10_Pomiar_w_kognitywistyce

Litaratura:

Isaac, A. M. (2013). Quantifying the subjective: Psychophysics and the geometry of color. Philosophical Psychology, 26(2), 207-233.

Michel, M. (2019). The Mismeasure of Consciousness: A problem of coordination for the Perceptual Awareness Scale. Philosophy of Science, 86(5), 1239-1249.

Runhardt, R.W. Reactivity in measuring depression. Euro Jnl Phil Sci 11, 77 (2021). https://doi.org/10.1007/s13194-021-00395-0

Literatura dodatkowa:

Michel, M. Calibration in Consciousness Science. Erkenn (2021). https://doi.org/10.1007/s10670-021-00383-z

Vessonen, E. (2020). The Complementarity of Psychometrics and the Representational Theory of Measurement. The British Journal for the Philosophy of Science, 71(2), 415–442.

Campbell, D. T., & Russo, M. J. (2001). Social measurement. SAGE Publications, Incorporated.

Chang, H. (2004). Inventing temperature: Measurement and scientific progress. Oxford University Press.

11_Dane w kognitywistyce

Literatura:

Ward, Z. B. (2020). Registration pluralism and the cartographic approach to data aggregation across brains. The British Journal for the Philosophy of Science, https://doi.org/10.1093/bjps/axz027

Wright, J. (2018). Seeing patterns in neuroimaging data. Progress in brain research, 243, 299-323.

Machery, E. (2021). A mistaken confidence in data. European Journal for Philosophy of Science, 11(2), 1-17.

Literatura dodatkowa:

Boyd, N. M. (2018). Evidence enriched. Philosophy of Science, 85(3), 403-421.

Leonelli, S. (2015). What counts as scientific data? A relational framework.

Philosophy of Science, 82(5), 810-821.

Lusk, G. (2020). Saving the Data. The British Journal for the Philosophy of Science.

Wright, J. (2021). Saving Data Analysis: Epistemic Friction and Progress in Neuroimaging Research. w: Neural Mechanisms, Springer, Cham, s.163-189.

Wright, J. (2018). The analysis of data and the evidential scope of neuroimaging results. The British Journal for the Philosophy of Science, 69(4), 1179-1203.

12_Teoria_w_kognitywistyce

Literatura:

Aktunc, M. E. (2019). Productive theory-ladenness in fMRI. Synthese, 1-17.

Hardcastle, V. G. (2007). The theoretical and methodological foundations of cognitive neuroscience. W: Philosophy of psychology and cognitive science. North-Holland, s.295-311.

Literatura dodatkowa:

Anderson, J. R. (1996). ACT: A simple theory of complex cognition. American psychologist, 51(4), 355.

Churchland, P. M. (1989). On the nature of theories: A neurocomputational perspective. Minnesota Studies in the Philosophy of Science, 14.

Craver, C. F. (2002). Structures of scientific theories. The Blackwell guide to the philosophy of science, 55-79.

Hochstein, E. (2019). How metaphysical commitments shape the study of psychological mechanisms. Theory & Psychology, 29(5), 579-600.

Smaldino, P. E. (2020). How to translate a verbal theory into a formal model. Social Psychology.

13_Podstawowe_pojęcia:_OBLICZANIE,_REPREZENTACJE_i_ INFORMACJA

Literatura:

Collins, A. (2007). From H= log sn to conceptual framework: a short history of information. History of Psychology, 10(1), 44.

Fresco, N. The Explanatory Role of Computation in Cognitive Science. Minds & Machines 22, 353–380 (2012).

Miłkowski, M. (2018). From computer metaphor to computational modeling: the evolution of computationalism. Minds and Machines, 28(3), 515-541.

Ramsey, W. (2017). Must cognition be representational?. Synthese, 194(11), 4197-4214.

Thomson, E., Piccinini, G. (2018). Neural representations observed. Minds and Machines, 28(1), 191-235.

Literatura dodatkowa:

Chemero, A. (2014). Antyreprezentacjonalizm i nastawienie dynamiczne tłum. P. Gładziejewski, Przegląd filozoficzno-literacki, 2(39), s. 79-107.

Fresco, N., Copeland, B.J. & Wolf, M.J. The indeterminacy of computation. Synthese (2021). https://doi.org/10.1007/s11229-021-03352-9

Milkowski, M. (2013). Explaining the computational mind. MIT Press.

Piccinini, G. (2015). Physical computation: A mechanistic account. OUP Oxford.

van Rooij, I. (2008). The Tractable Cognition thesis. Cognitive Science, 32, 939-984.

Shea, N. (2018). Representation in cognitive science. Oxford University Press.

14_Kognitywistyka_jako_interdyscyplinarny_obszar_badań

Literatura:

Núñez, R., Allen, M., Gao, R., Rigoli, C. M., Relaford-Doyle, J., & Semenuks, A. (2019). What happened to cognitive science? Nature Human Behaviour, 3, 782– 791.

Commentaries on Rafael Núñez’s article (2019), “What Happened to Cognitive Science?” (red.). Gray, W.D. Topics In Cognitive Science, 838-927.

Núñez, R., Allen, M., Gao, R., Miller Rigoli, C., Relaford-Doyle, J. and Semenuks, A. (2020), For the Sciences They Are A-Changin’: A Response to Commentaries on Núñez et al.’s (2019) “What Happened to Cognitive Science?”. Top Cogn Sci, 12: 790-803.

Mäki, U. (2016). Philosophy of interdisciplinarity. What? Why? How?. European Journal for Philosophy of Science, 6(3), 327-342.

Litaratura dodatkowa:

Cohen-Cole, J. (2007). Instituting the science of mind: intellectual economies and disciplinary exchange at Harvard's Center for Cognitive Studies. The British Journal for the History of Science, 40(4), s.567-597.

Derry, S.J, Schunn, C.D. & Gernsbacher M.A. (red.). Interdisciplinary collaboration: An emerging cognitive science. Mahwah, NJ: Erlbaum.

Gardner, H. (1987). The mind's new science: A history of the cognitive revolution. Basic books.

Graff, Harvey J. 2015. Undisciplining Knowledge: Interdisciplinarity in the Twentieth Century. Baltimore: Johns Hopkins University Press.

Klein, J. T. (2010). A taxonomy of interdisciplinarity. w: The Oxford handbook of interdisciplinarity, s.15-30.

15_Podsumowanie

Literatura (publikacje pomocnicze):

Anderson, J. A., & Rosenfeld, E. (Eds.). (2000). Talking nets: An oral history of neural networks. MiT Press.

Baars, B. J. (1986). The cognitive revolution in psychology. Guilford Press.

Bechtel, W. (1988). Philosophy of science: An overview for cognitive science. Lawrence Erlbaum Associates, Inc.

Bechtel, W., Graham, G., & Balota, D. A. (Eds.). (1998). A companion to cognitive science. Oxford: Blackwell.

Danziger, K. (1994). Constructing the subject: Historical origins of psychological research. Cambridge University Press.

Danziger, K. (2008). Marking the mind: A history of memory. New York, NY: Cambridge.

Derry, S.J, Schunn, C.D. & Gernsbacher M.A. (Eds.). Interdisciplinary collaboration: An emerging cognitive science. Mahwah, NJ: Erlbaum.

Chang, H. (2004). Inventing temperature: Measurement and scientific progress. Oxford University Press.

Hempel, C.G. (2001) Filozofia nauk przyrodniczych, tłum. Barbara Stanosz, Fundacja Aletheia, Kraków

Frankish, K., & Ramsey, W. (Eds.). (2012). The Cambridge handbook of cognitive science. Cambridge University Press.

Kuhn, T. Postscriptum (1969), w: Struktura rewolucji naukowych, tłum. Helena Ostromęcka, Fundacja Aletheia (dowolne wydanie)

Soler, L., Zwart, S., Lynch, M., & Israel-Jost, V. (Eds.). (2014). Science after the practice turn in the philosophy, history, and social studies of science. Routledge.

Wimsatt, W. (2007). Re-engineering philosophy for limited beings: Piecewise approximations to reality. Harvard University Press.

Uwagi:

Na zaliczneie przedmiotu skłąda się:

- aktywność na zajęciach;

- krótka praca omawiająca problem filozoficzny obecny w artykule kognitywistycznym;

Zajęcia w cyklu "Semestr zimowy 2022/23" (zakończony)

Okres: 2022-10-01 - 2023-02-19
Wybrany podział planu:
Przejdź do planu
Typ zajęć:
Konwersatorium, 30 godzin więcej informacji
Koordynatorzy: Przemysław Nowakowski
Prowadzący grup: Przemysław Nowakowski
Lista studentów: (nie masz dostępu)
Zaliczenie: Przedmiot - Zaliczenie na ocenę
Konwersatorium - Zaliczenie na ocenę
Skrócony opis:

Na zajęciach zajmiemy się podstawowymi zagadnieniami filozofii kognitywistyki, uprawianej w kontekście historycznego i praktycznego zwrotu w filozofii nauki. Omówimy zarówno historię rozwoju dyscypliny, jak i jej bieżące problemy.

Pełny opis:

Filozofia kognitywistyki, to wyróżniony przedmiotowo dział filozofii nauki. Na zajęciach będziemy przyglądać się z perspektywy historii i filozofii nauki takim kwestiom jak przedmiot badań kognitywistycznych (numery spotkań: 3,4,5); obecnym w kognitywistyce koncepcjom/rodzajom wyjaśniania (7,8); kontrowersjom wokół zintegrowania kognitywistyki (6,14). Ponadto przyjrzymy się filozoficznym badaniom nad eksperymentami, metodami & technikami, danymi czy rolą teorii w kognitywistyce (9,10,11,12), a także jej podstawowymi pojęciami (13).

Celem zajęć jest nie tylko zapoznanie uczestników z klasycznymi i aktualnymi problemami filozofii kognitywistyki, ale także, a może przede wszystkim, rozwinięcie właściwej dla filozofii nauki wrażliwości na filozoficzny wymiar problemów z jakimi mierzą się w swojej codziennej praktyce badawcze, tu: kognitywiści.

Literatura:

1_Zajęcia_wprowadzające

2_Historia_i_rozwój_kognitywistyki

Literatura:

Bechtel, W., Abrahamsen, A., & Graham, G. (2017). The life of cognitive science. W: Bechtel, W., Graham, G., & Balota, D. A. (red.). A companion to cognitive science Oxford: Blackwell. s.1-104.

Cohen-Cole, J. (2007). Instituting the science of mind: intellectual economies and disciplinary exchange at Harvard's Center for Cognitive Studies. The British Journal for the History of Science, 40(4), s.567-597.

Crowther‐Heyck, H. (2006). Herbert Simon and the GSIA: Building an interdisciplinary community. Journal of the History of the Behavioral Sciences, 42(4), s.311-334.

Literatura dodatkowa:

Gardner, H. (1987). The mind's new science: A history of the cognitive revolution. Basic books.

Graff, Harvey J. 2015. Undisciplining Knowledge: Interdisciplinarity in the Twentieth Century. Baltimore: Johns Hopkins University Press.

3_Czym_jest_poznanie?

Literatura:

Aizawa, K. (2017). Cognition and behavior. Synthese 194, 4269–4288.

Akagi, M. (2018). Rethinking the problem of cognition. Synthese 195, 3547–3570.

Allen, C. (2017). On (not) defining cognition. Synthese 194, 4233–4249.

Keijzer, F. (2021). Demarcating cognition: the cognitive life sciences. Synthese 198, 137–157.

Literatura dodatkowa:

Baum, C. (2016). Stabilizing Cognition: An STS Approach to the Sloan Foundation Report. Theory & Psychology, 26(6), 773-787.

Buckner, C., Fridland, E. (2017) What is cognition? angsty monism, permissive pluralism(s), and the future of cognitive science. Synthese 194, 4191–4195.

Buckner, C. (2015). A property cluster theory of cognition. Philosophical Psychology, 28(3), 307–336.

4_Przedmiot_badań_kognitywistycznych

Literatura:

Bogen, J., & Woodward, J. (1988). Saving the phenomena. The Philosophical Review, 97(3), 303-352.

Cummins, R. (2000). “How does it work?” vs. “What are the laws?” Two conceptions of psychological explanation. w: Keil, F., Wilson, R. (Eds.), Explanation and cognition. MIT Press, s.117-145.

Feest, U. (2017). Phenomena and objects of research in the cognitive and behavioral sciences. Philosophy of Science, 84(5), 1165-1176.

Literatura dodatkowa:

Danziger, K. (2003). Where history, theory, and philosophy meet: The biography of psychological objects. About psychology: Essays at the crossroads of history, theory, and philosophy, 19-33.

Nowakowski, P. R. (2019). Epistemic Challenges: Engaging Philosophically in Cognitive Science. Ruch Filozoficzny, 75(2).

Rheinberger H.­J. (2015). Epistemologia historyczna. tłum. Jan Surman, Warszawa: Oficyna Naukowa.

5_Rodzaje_naturalne_w kognitywistyce

Literatura:

Fedorenko, E., Blank, I. A. (2020). Broca’s area is not a natural kind. Trends in cognitive sciences, 24(4), 270-284.

Gomez-Lavin, J. (2021). Working memory is not a natural kind and cannot explain central cognition. Review of Philosophy and Psychology, 12(2), 199-225.

Taylor, H. (2018). Attention, psychology, and pluralism. The British Journal for the Philosophy of Science, 69(4), 935-956.

Barrett, L. F. (2006). Are emotions natural kinds?. Perspectives on psychological science, 1(1), 28-58.

Literatura dodatkowa:

Bird, Alexander and Emma Tobin, "Natural Kinds", The Stanford Encyclopedia of Philosophy (Spring 2018 Edition), Edward N. Zalta (ed.), URL = <https://plato.stanford.edu/archives/spr2018/entries/natural-kinds/>.

Boyd, R. (2013). Kinds as the “workmanship of men”: Realism, constructivism, and natural kinds. W: Rationalität, Realismus, Revision/Rationality, Realism, Revision, (red.) Nida-Rümelin, J. de Gruyter, s. 52-89.

Cheng, S., & Werning, M. (2016). What is episodic memory if it is a natural kind?. Synthese, 193(5), 1345-1385.

Hommel, B., Chapman, C. S., Cisek, P., Neyedli, H. F., Song, J. H., & Welsh, T. N. (2019). No one knows what attention is. Attention, Perception, & Psychophysics, 81(7), 2288-2303.

Keijzer, F. (2019). Is ‘the brain’a helpful metaphor for neuroscience?. Behavioral and Brain Sciences, 42, e234.

Michaelian, K. (2011). Is memory a natural kind?. Memory Studies, 4(2), 170-189.

Weidman, A. C., Steckler, C. M., & Tracy, J. L. (2017). The jingle and jangle of emotion assessment: Imprecise measurement, casual scale usage, and conceptual fuzziness in emotion research. Emotion, 17(2), 267.

6_Pluralizm a unifikacja w kognitywistyce

Litaratura:

Dale, R. (2008). The possibility of a pluralist cognitive science. Journal of Experimental and Theoretical Artificial Intelligence, 20(3), 155-179.

Miłkowski, M. (2016). Unification strategies in cognitive science. Studies in Logic, Grammar and Rhetoric, 48(1), 13-33.

Literatura dodatkowa:

Dale, R., Dietrich, E., & Chemero, A. (2009). Explanatory pluralism in cognitive science. Cognitive science, 33(5), 739-742.

Fodor, J. (1974/2008) Nauki szczegółowe (albo: niejednorodność nauk jako hipoteza robocza), tłum. Marcin Gokieli, w: Miłkowski, M., Poczobut, R. (red.). Analityczna metafizyka umysłu, Wydawnictwo IFiS PAN, Warszawa, s. 56-75.

Miłkowski, M., & Nowakowski, P. (2019). Representational unification in cognitive science: Is embodied cognition a unifying perspective?. Synthese, 1-22.

Potochnik, A., & Sanches de Oliveira, G. (2020). Patterns in cognitive phenomena and pluralism of explanatory styles. Topics in cognitive science, 12(4), 1306-1320.

7_Wyjaśnianie_w_kognitywistyce_1

Literatura:

Franks, B. (1995). On explanation in the cognitive sciences: Competence, idealization, and the failure of the classical cascade. The British journal for the philosophy of science, 46(4), 475-502.

Marraffa, M., & Paternoster, A. (2013). Functions, levels, and mechanisms: Explanation in cognitive science and its problems. Theory & Psychology, 23(1), 22-45.

Piccinini, G., & Craver, C. (2011). Integrating psychology and neuroscience: Functional analyses as mechanism sketches. Synthese, 183(3), 283-311.

Literatura dodatkowa:

Bechtel, W., & Shagrir, O. (2015). The non‐redundant contributions of Marr's three levels of analysis for explaining information‐processing mechanisms. Topics in Cognitive Science, 7(2), 312-322.

Shagrir, O. (2010). Marr on computational-level theories. Philosophy of science, 77(4), 477-500.

8_Wyjaśnianie_kognitywistyce_2

Literatura:

Bertolero, M. A., & Bassett, D. S. (2020). On the nature of explanations offered by network science: A perspective from and for practicing neuroscientists. Topics in Cognitive Science, 12(4), 1272-1293.

Stepp, N., Chemero, A. and Turvey, M.T. (2011), Philosophy for the Rest of Cognitive Science. Topics in Cognitive Science, 3: 425-437.

Literatura dodatkowa:

Craver, C. F. (2016). The explanatory power of network models. Philosophy of Science, 83(5), 698-709.

Faskowitz, J., Betzel, R. F., & Sporns, O. (2021). Edges in brain networks: Contributions to models of structure and function. Network Neuroscience. Advance publication. https://doi.org/10.1162/netn_a_00204

Zednik, C. (2011). The nature of dynamical explanation. Philosophy of Science, 78(2), 238-263.

9_Filozofia_eksperymentu_w_kognitywistyce_a_różne_metody/techniki_badawcze

Literatura:

Bechtel, W. (2002). Aligning multiple research techniques in cognitive neuroscience: Why is it important?. Philosophy of Science, 69(S3), S48-S58.

Bickle, J. (2018). From microscopes to optogenetics: Ian Hacking vindicated. Philosophy of Science, 85(5), 1065-1077.

Sullivan, J. A. (2009). The multiplicity of experimental protocols: a challenge to reductionist and non-reductionist models of the unity of neuroscience. Synthese, 167(3), 511-539.

Literatura dodatkowa:

Bechtel, William (2000), “From Imaging to Believing: Epistemic Issues in Generating Bio- logical Data”, w: R. Creath and J. Maienschein (red.), Biology and Epistemology. Cam- bridge: Cambridge University Press, s.138–163.

Hanson, S. J. E., & Bunzl, M. E. (2010). Foundational issues in human brain mapping. MIT Press.

Ritchie, J. B., Kaplan, D. M., & Klein, C. (2019). Decoding the brain: Neural representation and the limits of multivariate pattern analysis in cognitive neuroscience. The British journal for the philosophy of science, 70(2), 581-607.

Stufflebeam, R. S., & Bechtel, W. (1997). PET: Exploring the Myth and the Method. Philosophy of Science, 64, S95-S106.

Sullivan, J. A. (2018). Optogenetics, pluralism, and progress. Philosophy of Science, 85(5), 1090-1101.

10_Pomiar_w_kognitywistyce

Litaratura:

Isaac, A. M. (2013). Quantifying the subjective: Psychophysics and the geometry of color. Philosophical Psychology, 26(2), 207-233.

Michel, M. (2019). The Mismeasure of Consciousness: A problem of coordination for the Perceptual Awareness Scale. Philosophy of Science, 86(5), 1239-1249.

Runhardt, R.W. Reactivity in measuring depression. Euro Jnl Phil Sci 11, 77 (2021). https://doi.org/10.1007/s13194-021-00395-0

Literatura dodatkowa:

Michel, M. Calibration in Consciousness Science. Erkenn (2021). https://doi.org/10.1007/s10670-021-00383-z

Vessonen, E. (2020). The Complementarity of Psychometrics and the Representational Theory of Measurement. The British Journal for the Philosophy of Science, 71(2), 415–442.

Campbell, D. T., & Russo, M. J. (2001). Social measurement. SAGE Publications, Incorporated.

Chang, H. (2004). Inventing temperature: Measurement and scientific progress. Oxford University Press.

11_Dane w kognitywistyce

Literatura:

Ward, Z. B. (2020). Registration pluralism and the cartographic approach to data aggregation across brains. The British Journal for the Philosophy of Science, https://doi.org/10.1093/bjps/axz027

Wright, J. (2018). Seeing patterns in neuroimaging data. Progress in brain research, 243, 299-323.

Machery, E. (2021). A mistaken confidence in data. European Journal for Philosophy of Science, 11(2), 1-17.

Literatura dodatkowa:

Boyd, N. M. (2018). Evidence enriched. Philosophy of Science, 85(3), 403-421.

Leonelli, S. (2015). What counts as scientific data? A relational framework.

Philosophy of Science, 82(5), 810-821.

Lusk, G. (2020). Saving the Data. The British Journal for the Philosophy of Science.

Wright, J. (2021). Saving Data Analysis: Epistemic Friction and Progress in Neuroimaging Research. w: Neural Mechanisms, Springer, Cham, s.163-189.

Wright, J. (2018). The analysis of data and the evidential scope of neuroimaging results. The British Journal for the Philosophy of Science, 69(4), 1179-1203.

12_Teoria_w_kognitywistyce

Literatura:

Aktunc, M. E. (2019). Productive theory-ladenness in fMRI. Synthese, 1-17.

Hardcastle, V. G. (2007). The theoretical and methodological foundations of cognitive neuroscience. W: Philosophy of psychology and cognitive science. North-Holland, s.295-311.

Literatura dodatkowa:

Anderson, J. R. (1996). ACT: A simple theory of complex cognition. American psychologist, 51(4), 355.

Churchland, P. M. (1989). On the nature of theories: A neurocomputational perspective. Minnesota Studies in the Philosophy of Science, 14.

Craver, C. F. (2002). Structures of scientific theories. The Blackwell guide to the philosophy of science, 55-79.

Hochstein, E. (2019). How metaphysical commitments shape the study of psychological mechanisms. Theory & Psychology, 29(5), 579-600.

Smaldino, P. E. (2020). How to translate a verbal theory into a formal model. Social Psychology.

13_Podstawowe_pojęcia:_OBLICZANIE,_REPREZENTACJE_i_ INFORMACJA

Literatura:

Collins, A. (2007). From H= log sn to conceptual framework: a short history of information. History of Psychology, 10(1), 44.

Fresco, N. The Explanatory Role of Computation in Cognitive Science. Minds & Machines 22, 353–380 (2012).

Miłkowski, M. (2018). From computer metaphor to computational modeling: the evolution of computationalism. Minds and Machines, 28(3), 515-541.

Ramsey, W. (2017). Must cognition be representational?. Synthese, 194(11), 4197-4214.

Thomson, E., Piccinini, G. (2018). Neural representations observed. Minds and Machines, 28(1), 191-235.

Literatura dodatkowa:

Chemero, A. (2014). Antyreprezentacjonalizm i nastawienie dynamiczne tłum. P. Gładziejewski, Przegląd filozoficzno-literacki, 2(39), s. 79-107.

Fresco, N., Copeland, B.J. & Wolf, M.J. The indeterminacy of computation. Synthese (2021). https://doi.org/10.1007/s11229-021-03352-9

Milkowski, M. (2013). Explaining the computational mind. MIT Press.

Piccinini, G. (2015). Physical computation: A mechanistic account. OUP Oxford.

van Rooij, I. (2008). The Tractable Cognition thesis. Cognitive Science, 32, 939-984.

Shea, N. (2018). Representation in cognitive science. Oxford University Press.

14_Kognitywistyka_jako_interdyscyplinarny_obszar_badań

Literatura:

Núñez, R., Allen, M., Gao, R., Rigoli, C. M., Relaford-Doyle, J., & Semenuks, A. (2019). What happened to cognitive science? Nature Human Behaviour, 3, 782– 791.

Commentaries on Rafael Núñez’s article (2019), “What Happened to Cognitive Science?” (red.). Gray, W.D. Topics In Cognitive Science, 838-927.

Núñez, R., Allen, M., Gao, R., Miller Rigoli, C., Relaford-Doyle, J. and Semenuks, A. (2020), For the Sciences They Are A-Changin’: A Response to Commentaries on Núñez et al.’s (2019) “What Happened to Cognitive Science?”. Top Cogn Sci, 12: 790-803.

Mäki, U. (2016). Philosophy of interdisciplinarity. What? Why? How?. European Journal for Philosophy of Science, 6(3), 327-342.

Litaratura dodatkowa:

Cohen-Cole, J. (2007). Instituting the science of mind: intellectual economies and disciplinary exchange at Harvard's Center for Cognitive Studies. The British Journal for the History of Science, 40(4), s.567-597.

Derry, S.J, Schunn, C.D. & Gernsbacher M.A. (red.). Interdisciplinary collaboration: An emerging cognitive science. Mahwah, NJ: Erlbaum.

Gardner, H. (1987). The mind's new science: A history of the cognitive revolution. Basic books.

Graff, Harvey J. 2015. Undisciplining Knowledge: Interdisciplinarity in the Twentieth Century. Baltimore: Johns Hopkins University Press.

Klein, J. T. (2010). A taxonomy of interdisciplinarity. w: The Oxford handbook of interdisciplinarity, s.15-30.

15_Podsumowanie

Literatura (publikacje pomocnicze):

Anderson, J. A., & Rosenfeld, E. (Eds.). (2000). Talking nets: An oral history of neural networks. MiT Press.

Baars, B. J. (1986). The cognitive revolution in psychology. Guilford Press.

Bechtel, W. (1988). Philosophy of science: An overview for cognitive science. Lawrence Erlbaum Associates, Inc.

Bechtel, W., Graham, G., & Balota, D. A. (Eds.). (1998). A companion to cognitive science. Oxford: Blackwell.

Danziger, K. (1994). Constructing the subject: Historical origins of psychological research. Cambridge University Press.

Danziger, K. (2008). Marking the mind: A history of memory. New York, NY: Cambridge.

Derry, S.J, Schunn, C.D. & Gernsbacher M.A. (Eds.). Interdisciplinary collaboration: An emerging cognitive science. Mahwah, NJ: Erlbaum.

Chang, H. (2004). Inventing temperature: Measurement and scientific progress. Oxford University Press.

Hempel, C.G. (2001) Filozofia nauk przyrodniczych, tłum. Barbara Stanosz, Fundacja Aletheia, Kraków

Frankish, K., & Ramsey, W. (Eds.). (2012). The Cambridge handbook of cognitive science. Cambridge University Press.

Kuhn, T. Postscriptum (1969), w: Struktura rewolucji naukowych, tłum. Helena Ostromęcka, Fundacja Aletheia (dowolne wydanie)

Soler, L., Zwart, S., Lynch, M., & Israel-Jost, V. (Eds.). (2014). Science after the practice turn in the philosophy, history, and social studies of science. Routledge.

Wimsatt, W. (2007). Re-engineering philosophy for limited beings: Piecewise approximations to reality. Harvard University Press.

Uwagi:

Na zaliczneie przedmiotu skłąda się:

- aktywność na zajęciach;

- krótka praca omawiająca problem filozoficzny obecny w artykule kognitywistycznym;

Zajęcia w cyklu "Semestr zimowy 2023/24" (zakończony)

Okres: 2023-10-01 - 2024-02-19
Wybrany podział planu:
Przejdź do planu
Typ zajęć:
Konwersatorium, 30 godzin więcej informacji
Koordynatorzy: Przemysław Nowakowski
Prowadzący grup: Przemysław Nowakowski
Lista studentów: (nie masz dostępu)
Zaliczenie: Przedmiot - Zaliczenie na ocenę
Konwersatorium - Zaliczenie na ocenę
Skrócony opis:

Na zajęciach zajmiemy się podstawowymi zagadnieniami filozofii kognitywistyki, uprawianej w kontekście historycznego i praktycznego zwrotu w filozofii nauki. Omówimy zarówno historię rozwoju dyscypliny, jak i jej bieżące problemy.

Pełny opis:

Filozofia kognitywistyki, to wyróżniony przedmiotowo dział filozofii nauki. Na zajęciach będziemy przyglądać się z perspektywy historii i filozofii nauki takim kwestiom jak przedmiot badań kognitywistycznych (numery spotkań: 3,4,5); obecnym w kognitywistyce koncepcjom/rodzajom wyjaśniania (7,8); kontrowersjom wokół zintegrowania kognitywistyki (6,14). Ponadto przyjrzymy się filozoficznym badaniom nad eksperymentami, metodami & technikami, danymi czy rolą teorii w kognitywistyce (9,10,11,12), a także jej podstawowymi pojęciami (13).

Celem zajęć jest nie tylko zapoznanie uczestników z klasycznymi i aktualnymi problemami filozofii kognitywistyki, ale także, a może przede wszystkim, rozwinięcie właściwej dla filozofii nauki wrażliwości na filozoficzny wymiar problemów z jakimi mierzą się w swojej codziennej praktyce badawcze, tu: kognitywiści.

Literatura:

1_Zajęcia_wprowadzające

2_Historia_i_rozwój_kognitywistyki

Literatura:

Bechtel, W., Abrahamsen, A., & Graham, G. (2017). The life of cognitive science. W: Bechtel, W., Graham, G., & Balota, D. A. (red.). A companion to cognitive science Oxford: Blackwell. s.1-104.

Cohen-Cole, J. (2007). Instituting the science of mind: intellectual economies and disciplinary exchange at Harvard's Center for Cognitive Studies. The British Journal for the History of Science, 40(4), s.567-597.

Crowther‐Heyck, H. (2006). Herbert Simon and the GSIA: Building an interdisciplinary community. Journal of the History of the Behavioral Sciences, 42(4), s.311-334.

Literatura dodatkowa:

Gardner, H. (1987). The mind's new science: A history of the cognitive revolution. Basic books.

Graff, Harvey J. 2015. Undisciplining Knowledge: Interdisciplinarity in the Twentieth Century. Baltimore: Johns Hopkins University Press.

3_Czym_jest_poznanie?

Literatura:

Aizawa, K. (2017). Cognition and behavior. Synthese 194, 4269–4288.

Akagi, M. (2018). Rethinking the problem of cognition. Synthese 195, 3547–3570.

Allen, C. (2017). On (not) defining cognition. Synthese 194, 4233–4249.

Keijzer, F. (2021). Demarcating cognition: the cognitive life sciences. Synthese 198, 137–157.

Literatura dodatkowa:

Baum, C. (2016). Stabilizing Cognition: An STS Approach to the Sloan Foundation Report. Theory & Psychology, 26(6), 773-787.

Buckner, C., Fridland, E. (2017) What is cognition? angsty monism, permissive pluralism(s), and the future of cognitive science. Synthese 194, 4191–4195.

Buckner, C. (2015). A property cluster theory of cognition. Philosophical Psychology, 28(3), 307–336.

4_Przedmiot_badań_kognitywistycznych

Literatura:

Bogen, J., & Woodward, J. (1988). Saving the phenomena. The Philosophical Review, 97(3), 303-352.

Cummins, R. (2000). “How does it work?” vs. “What are the laws?” Two conceptions of psychological explanation. w: Keil, F., Wilson, R. (Eds.), Explanation and cognition. MIT Press, s.117-145.

Feest, U. (2017). Phenomena and objects of research in the cognitive and behavioral sciences. Philosophy of Science, 84(5), 1165-1176.

Literatura dodatkowa:

Danziger, K. (2003). Where history, theory, and philosophy meet: The biography of psychological objects. About psychology: Essays at the crossroads of history, theory, and philosophy, 19-33.

Nowakowski, P. R. (2019). Epistemic Challenges: Engaging Philosophically in Cognitive Science. Ruch Filozoficzny, 75(2).

Rheinberger H.­J. (2015). Epistemologia historyczna. tłum. Jan Surman, Warszawa: Oficyna Naukowa.

5_Rodzaje_naturalne_w kognitywistyce

Literatura:

Fedorenko, E., Blank, I. A. (2020). Broca’s area is not a natural kind. Trends in cognitive sciences, 24(4), 270-284.

Gomez-Lavin, J. (2021). Working memory is not a natural kind and cannot explain central cognition. Review of Philosophy and Psychology, 12(2), 199-225.

Taylor, H. (2018). Attention, psychology, and pluralism. The British Journal for the Philosophy of Science, 69(4), 935-956.

Barrett, L. F. (2006). Are emotions natural kinds?. Perspectives on psychological science, 1(1), 28-58.

Literatura dodatkowa:

Bird, Alexander and Emma Tobin, "Natural Kinds", The Stanford Encyclopedia of Philosophy (Spring 2018 Edition), Edward N. Zalta (ed.), URL = <https://plato.stanford.edu/archives/spr2018/entries/natural-kinds/>.

Boyd, R. (2013). Kinds as the “workmanship of men”: Realism, constructivism, and natural kinds. W: Rationalität, Realismus, Revision/Rationality, Realism, Revision, (red.) Nida-Rümelin, J. de Gruyter, s. 52-89.

Cheng, S., & Werning, M. (2016). What is episodic memory if it is a natural kind?. Synthese, 193(5), 1345-1385.

Hommel, B., Chapman, C. S., Cisek, P., Neyedli, H. F., Song, J. H., & Welsh, T. N. (2019). No one knows what attention is. Attention, Perception, & Psychophysics, 81(7), 2288-2303.

Keijzer, F. (2019). Is ‘the brain’a helpful metaphor for neuroscience?. Behavioral and Brain Sciences, 42, e234.

Michaelian, K. (2011). Is memory a natural kind?. Memory Studies, 4(2), 170-189.

Weidman, A. C., Steckler, C. M., & Tracy, J. L. (2017). The jingle and jangle of emotion assessment: Imprecise measurement, casual scale usage, and conceptual fuzziness in emotion research. Emotion, 17(2), 267.

6_Pluralizm a unifikacja w kognitywistyce

Litaratura:

Dale, R. (2008). The possibility of a pluralist cognitive science. Journal of Experimental and Theoretical Artificial Intelligence, 20(3), 155-179.

Miłkowski, M. (2016). Unification strategies in cognitive science. Studies in Logic, Grammar and Rhetoric, 48(1), 13-33.

Literatura dodatkowa:

Dale, R., Dietrich, E., & Chemero, A. (2009). Explanatory pluralism in cognitive science. Cognitive science, 33(5), 739-742.

Fodor, J. (1974/2008) Nauki szczegółowe (albo: niejednorodność nauk jako hipoteza robocza), tłum. Marcin Gokieli, w: Miłkowski, M., Poczobut, R. (red.). Analityczna metafizyka umysłu, Wydawnictwo IFiS PAN, Warszawa, s. 56-75.

Miłkowski, M., & Nowakowski, P. (2019). Representational unification in cognitive science: Is embodied cognition a unifying perspective?. Synthese, 1-22.

Potochnik, A., & Sanches de Oliveira, G. (2020). Patterns in cognitive phenomena and pluralism of explanatory styles. Topics in cognitive science, 12(4), 1306-1320.

7_Wyjaśnianie_w_kognitywistyce_1

Literatura:

Franks, B. (1995). On explanation in the cognitive sciences: Competence, idealization, and the failure of the classical cascade. The British journal for the philosophy of science, 46(4), 475-502.

Marraffa, M., & Paternoster, A. (2013). Functions, levels, and mechanisms: Explanation in cognitive science and its problems. Theory & Psychology, 23(1), 22-45.

Piccinini, G., & Craver, C. (2011). Integrating psychology and neuroscience: Functional analyses as mechanism sketches. Synthese, 183(3), 283-311.

Literatura dodatkowa:

Bechtel, W., & Shagrir, O. (2015). The non‐redundant contributions of Marr's three levels of analysis for explaining information‐processing mechanisms. Topics in Cognitive Science, 7(2), 312-322.

Shagrir, O. (2010). Marr on computational-level theories. Philosophy of science, 77(4), 477-500.

8_Wyjaśnianie_kognitywistyce_2

Literatura:

Bertolero, M. A., & Bassett, D. S. (2020). On the nature of explanations offered by network science: A perspective from and for practicing neuroscientists. Topics in Cognitive Science, 12(4), 1272-1293.

Stepp, N., Chemero, A. and Turvey, M.T. (2011), Philosophy for the Rest of Cognitive Science. Topics in Cognitive Science, 3: 425-437.

Literatura dodatkowa:

Craver, C. F. (2016). The explanatory power of network models. Philosophy of Science, 83(5), 698-709.

Faskowitz, J., Betzel, R. F., & Sporns, O. (2021). Edges in brain networks: Contributions to models of structure and function. Network Neuroscience. Advance publication. https://doi.org/10.1162/netn_a_00204

Zednik, C. (2011). The nature of dynamical explanation. Philosophy of Science, 78(2), 238-263.

9_Filozofia_eksperymentu_w_kognitywistyce_a_różne_metody/techniki_badawcze

Literatura:

Bechtel, W. (2002). Aligning multiple research techniques in cognitive neuroscience: Why is it important?. Philosophy of Science, 69(S3), S48-S58.

Bickle, J. (2018). From microscopes to optogenetics: Ian Hacking vindicated. Philosophy of Science, 85(5), 1065-1077.

Sullivan, J. A. (2009). The multiplicity of experimental protocols: a challenge to reductionist and non-reductionist models of the unity of neuroscience. Synthese, 167(3), 511-539.

Literatura dodatkowa:

Bechtel, William (2000), “From Imaging to Believing: Epistemic Issues in Generating Bio- logical Data”, w: R. Creath and J. Maienschein (red.), Biology and Epistemology. Cam- bridge: Cambridge University Press, s.138–163.

Hanson, S. J. E., & Bunzl, M. E. (2010). Foundational issues in human brain mapping. MIT Press.

Ritchie, J. B., Kaplan, D. M., & Klein, C. (2019). Decoding the brain: Neural representation and the limits of multivariate pattern analysis in cognitive neuroscience. The British journal for the philosophy of science, 70(2), 581-607.

Stufflebeam, R. S., & Bechtel, W. (1997). PET: Exploring the Myth and the Method. Philosophy of Science, 64, S95-S106.

Sullivan, J. A. (2018). Optogenetics, pluralism, and progress. Philosophy of Science, 85(5), 1090-1101.

10_Pomiar_w_kognitywistyce

Litaratura:

Isaac, A. M. (2013). Quantifying the subjective: Psychophysics and the geometry of color. Philosophical Psychology, 26(2), 207-233.

Michel, M. (2019). The Mismeasure of Consciousness: A problem of coordination for the Perceptual Awareness Scale. Philosophy of Science, 86(5), 1239-1249.

Runhardt, R.W. Reactivity in measuring depression. Euro Jnl Phil Sci 11, 77 (2021). https://doi.org/10.1007/s13194-021-00395-0

Literatura dodatkowa:

Michel, M. Calibration in Consciousness Science. Erkenn (2021). https://doi.org/10.1007/s10670-021-00383-z

Vessonen, E. (2020). The Complementarity of Psychometrics and the Representational Theory of Measurement. The British Journal for the Philosophy of Science, 71(2), 415–442.

Campbell, D. T., & Russo, M. J. (2001). Social measurement. SAGE Publications, Incorporated.

Chang, H. (2004). Inventing temperature: Measurement and scientific progress. Oxford University Press.

11_Dane w kognitywistyce

Literatura:

Ward, Z. B. (2020). Registration pluralism and the cartographic approach to data aggregation across brains. The British Journal for the Philosophy of Science, https://doi.org/10.1093/bjps/axz027

Wright, J. (2018). Seeing patterns in neuroimaging data. Progress in brain research, 243, 299-323.

Machery, E. (2021). A mistaken confidence in data. European Journal for Philosophy of Science, 11(2), 1-17.

Literatura dodatkowa:

Boyd, N. M. (2018). Evidence enriched. Philosophy of Science, 85(3), 403-421.

Leonelli, S. (2015). What counts as scientific data? A relational framework.

Philosophy of Science, 82(5), 810-821.

Lusk, G. (2020). Saving the Data. The British Journal for the Philosophy of Science.

Wright, J. (2021). Saving Data Analysis: Epistemic Friction and Progress in Neuroimaging Research. w: Neural Mechanisms, Springer, Cham, s.163-189.

Wright, J. (2018). The analysis of data and the evidential scope of neuroimaging results. The British Journal for the Philosophy of Science, 69(4), 1179-1203.

12_Teoria_w_kognitywistyce

Literatura:

Aktunc, M. E. (2019). Productive theory-ladenness in fMRI. Synthese, 1-17.

Hardcastle, V. G. (2007). The theoretical and methodological foundations of cognitive neuroscience. W: Philosophy of psychology and cognitive science. North-Holland, s.295-311.

Literatura dodatkowa:

Anderson, J. R. (1996). ACT: A simple theory of complex cognition. American psychologist, 51(4), 355.

Churchland, P. M. (1989). On the nature of theories: A neurocomputational perspective. Minnesota Studies in the Philosophy of Science, 14.

Craver, C. F. (2002). Structures of scientific theories. The Blackwell guide to the philosophy of science, 55-79.

Hochstein, E. (2019). How metaphysical commitments shape the study of psychological mechanisms. Theory & Psychology, 29(5), 579-600.

Smaldino, P. E. (2020). How to translate a verbal theory into a formal model. Social Psychology.

13_Podstawowe_pojęcia:_OBLICZANIE,_REPREZENTACJE_i_ INFORMACJA

Literatura:

Collins, A. (2007). From H= log sn to conceptual framework: a short history of information. History of Psychology, 10(1), 44.

Fresco, N. The Explanatory Role of Computation in Cognitive Science. Minds & Machines 22, 353–380 (2012).

Miłkowski, M. (2018). From computer metaphor to computational modeling: the evolution of computationalism. Minds and Machines, 28(3), 515-541.

Ramsey, W. (2017). Must cognition be representational?. Synthese, 194(11), 4197-4214.

Thomson, E., Piccinini, G. (2018). Neural representations observed. Minds and Machines, 28(1), 191-235.

Literatura dodatkowa:

Chemero, A. (2014). Antyreprezentacjonalizm i nastawienie dynamiczne tłum. P. Gładziejewski, Przegląd filozoficzno-literacki, 2(39), s. 79-107.

Fresco, N., Copeland, B.J. & Wolf, M.J. The indeterminacy of computation. Synthese (2021). https://doi.org/10.1007/s11229-021-03352-9

Milkowski, M. (2013). Explaining the computational mind. MIT Press.

Piccinini, G. (2015). Physical computation: A mechanistic account. OUP Oxford.

van Rooij, I. (2008). The Tractable Cognition thesis. Cognitive Science, 32, 939-984.

Shea, N. (2018). Representation in cognitive science. Oxford University Press.

14_Kognitywistyka_jako_interdyscyplinarny_obszar_badań

Literatura:

Núñez, R., Allen, M., Gao, R., Rigoli, C. M., Relaford-Doyle, J., & Semenuks, A. (2019). What happened to cognitive science? Nature Human Behaviour, 3, 782– 791.

Commentaries on Rafael Núñez’s article (2019), “What Happened to Cognitive Science?” (red.). Gray, W.D. Topics In Cognitive Science, 838-927.

Núñez, R., Allen, M., Gao, R., Miller Rigoli, C., Relaford-Doyle, J. and Semenuks, A. (2020), For the Sciences They Are A-Changin’: A Response to Commentaries on Núñez et al.’s (2019) “What Happened to Cognitive Science?”. Top Cogn Sci, 12: 790-803.

Mäki, U. (2016). Philosophy of interdisciplinarity. What? Why? How?. European Journal for Philosophy of Science, 6(3), 327-342.

Litaratura dodatkowa:

Cohen-Cole, J. (2007). Instituting the science of mind: intellectual economies and disciplinary exchange at Harvard's Center for Cognitive Studies. The British Journal for the History of Science, 40(4), s.567-597.

Derry, S.J, Schunn, C.D. & Gernsbacher M.A. (red.). Interdisciplinary collaboration: An emerging cognitive science. Mahwah, NJ: Erlbaum.

Gardner, H. (1987). The mind's new science: A history of the cognitive revolution. Basic books.

Graff, Harvey J. 2015. Undisciplining Knowledge: Interdisciplinarity in the Twentieth Century. Baltimore: Johns Hopkins University Press.

Klein, J. T. (2010). A taxonomy of interdisciplinarity. w: The Oxford handbook of interdisciplinarity, s.15-30.

15_Podsumowanie

Literatura (publikacje pomocnicze):

Anderson, J. A., & Rosenfeld, E. (Eds.). (2000). Talking nets: An oral history of neural networks. MiT Press.

Baars, B. J. (1986). The cognitive revolution in psychology. Guilford Press.

Bechtel, W. (1988). Philosophy of science: An overview for cognitive science. Lawrence Erlbaum Associates, Inc.

Bechtel, W., Graham, G., & Balota, D. A. (Eds.). (1998). A companion to cognitive science. Oxford: Blackwell.

Danziger, K. (1994). Constructing the subject: Historical origins of psychological research. Cambridge University Press.

Danziger, K. (2008). Marking the mind: A history of memory. New York, NY: Cambridge.

Derry, S.J, Schunn, C.D. & Gernsbacher M.A. (Eds.). Interdisciplinary collaboration: An emerging cognitive science. Mahwah, NJ: Erlbaum.

Chang, H. (2004). Inventing temperature: Measurement and scientific progress. Oxford University Press.

Hempel, C.G. (2001) Filozofia nauk przyrodniczych, tłum. Barbara Stanosz, Fundacja Aletheia, Kraków

Frankish, K., & Ramsey, W. (Eds.). (2012). The Cambridge handbook of cognitive science. Cambridge University Press.

Kuhn, T. Postscriptum (1969), w: Struktura rewolucji naukowych, tłum. Helena Ostromęcka, Fundacja Aletheia (dowolne wydanie)

Soler, L., Zwart, S., Lynch, M., & Israel-Jost, V. (Eds.). (2014). Science after the practice turn in the philosophy, history, and social studies of science. Routledge.

Wimsatt, W. (2007). Re-engineering philosophy for limited beings: Piecewise approximations to reality. Harvard University Press.

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