Cognitive neuroscience

GRAZIA FERNANDA SPITONI
ANTONIO CHIRUMBOLO

The aim of this course is to give the students all the fundamentals to carry on an experimental study, from basic bibliographic research to the final writing of a paper.

The classes will allow the students to manage the main neuroscientific issue necessary in the experimental research field: bibliographic research, hypothesis formulation, sample size, data collecting, preliminary analyses, descriptive analyses, inferential analyses, results’ writing and interpretation
knowledge and understanding:
At the end of the course, students will be able to develop an experimental hypothesis as well as to carry on an experimental study. Also, students will gain abilities in the critical reading of scientific papers.
applying knowledge and understanding:
Through active study, students will be able to apply knowledge and understanding in a other labs and with other researchers.
making judgements:
Thanks to the critical discussion, the students will be able to manage experimental complexity, elaborate alternative solutions and make inferences on the results of the studies.
communication skills:
The students will learn how to communicate their findings both in the oral then in the written form
learning skills:
Finally, the course pays particular attention to teach to the students how to independently work in the statistical analyses.

Students will be expected to acquire theoretical and conceptual knowledge related to the topics covered in the course, to carry out applied exercises, and to orient themselves within a research problem or question by identifying the most appropriate methodologies and analyses to perform and interpret. They will also be expected to demonstrate critical reasoning skills in the choice of procedures, in the reading of results, and in the evaluation of their coherence with the objectives of the research.
In particular, they will be expected to:
a) know the basic concepts and possess the theoretical knowledge of the discipline;
b) be able to carry out exercises and solve methodological and statistical problems;
c) understand the processes underlying the discipline, such as designing a research study and statistical decision-making;
d) demonstrate critical reasoning skills, for example by identifying and applying the correct statistical analysis in response to a specific research question or research design.

Basic mathematical competences provided at school will be necessary. A Psychometric course given during BA is to be preferable.

The course is divided into two distinct parts: one covering research methods in Cognitive Neuroscience and a more specifically statistical laboratory part.
The methodological part will cover the following topics: use of search engines for literature searches; types of papers and meta-analysis; validity of experimental studies; types of experimental designs; the single case; hypothesis formulation; sample size; data collection methods; interpretation of results; and the use of various graphs.
The laboratory deals with statistical methods for quantitative research in Psychology, using the software jamovi, and consists of four different teaching units. In the first part, basic descriptive statistics and measurement theory will be briefly recalled (students should be already familiar with them from previous basic courses). The second and the third part regards inferential statistics: basic concepts, univariate and multivariate data analyses. The fourth part concerns of relations among variables. The statistical software jamovi will be applied to illustrate those data analysis techniques. In particular, the topics that the laboratory will explore are the following.
In the first part of the laboratory, we briefly recall descriptive statistics. The main topics are: Frequency distributions and tables; graphical representation of the data (e.g., histogram, bar-graph, chart-pie, line-graph ...); measures of central tendency (e.g., mode, median, mean); measures of dispersion (e.g., range, variance, standard deviation); positioning indexes (e.g., percentiles, quartiles, deciles ...); the normal curve; the standardized normal curve distribution; standardization of scores (e.g., z-scores, IQ deviation, T-scores ...).
In the second part, we introduce inferential statistics and hypothesis testing. The main topics are: populations and samples; parameters and statistical indexes; different sampling techniques; the concept of probability; inferential statistics; parameters estimate: confidence intervals; hypothesis testing and statistical decision making; type error I and II; level of significance and p-value; statistical power and power analysis.
In the third part, we deal on hypothesis testing on means. Hypothesis testing on two means: independent samples t-tests; Welch t-test for unequal variances groups; paired samples t-tests; one sample t-tests. Hypothesis testing on more than two means: models of Analysis of Variance (ANOVA). One-way ANOVA; factorial ANOVA; ANOVA with repeated measures; ANOVA for mixed designs (between and within factors); MANOVA; Analysis of Covariance.
The fourth part will deal with the relationships between variables: bivariate correlation and linear regression.
All statistical analyses will be explained and illustrated with practical exercises using the statistical software jamovi.

For the methodological part of the program:
McBurney, D. H., & White, T. L. (2007). Research methods (7th ed.). Thomson/Wadsworth.
Kazdin, A. E. (2016). Research design in clinical psychology (5th ed.). Pearson.
For the statistical part of the program:
Theory: Howitt, D., & Cramer, D. (2011). Introduction to statistics in psychology (Fifth Edition). Edinburgh, UK: Pearson Education. (not-to-do chapt. 27, 29, 30, 32, 33, 35, 36, 38, 40, 41, 42)
Jamovi: One of the following:
a) Navarro DJ and Foxcroft DR (2022). learning statistics with jamovi: a tutorial for psychology students and other beginners. (Version 0.75). DOI: 10.24384/hgc3-7p15 (not-to-do chapt. 10, 16, 17)
Available for free at: https://www.learnstatswithjamovi.com/
b) Richardson, P., & Machan, L. (2021). Jamovi for Psychologists. Bloomsbury Publishing.

Theoretical lectures in the classroom aim to teach the basic theoretical concepts and knowledge of the discipline. Exercises and practical activities are designed to apply these concepts and knowledge in practice. The course will be held in the classroom; online or blended learning will not be offered unless otherwise specified by the authorities.

The course will be delivered in presence. Attending of the lessons is facultative but strongly encourages. Students who attend the course usually perform significantly better.

The exam consists of a written test consisting of multiple-choice questions. Each question has only one correct answer. One point is awarded for each correct answer, while incorrect answers are not penalized. The questions are designed to assess: a) basic theoretical knowledge of the discipline covered in the program; b) the ability to solve problems and exercises practically; c) understanding of the processes involved in designing neuroscience research and analyzing data (e.g., research design, hypothesis testing, statistical decision-making); d) critical reasoning skills (e.g., identifying and applying the correct statistical methodology and analysis in relation to a specific research question or problem); and proficiency in reading graphs, statistical outputs, and statistical inputs.

Multiple regression analysis is deemed to:
a) compare the means of different groups
b) analysis the bivariate relation between two variables
c) study the impact of a set of predictors on a given outcome
d) predict the score more than two outcomes from a single predictor

• Research methods in Cognitive Neuroscience


• Data Analysis in Cognitive Neuroscience