Advanced Neuroscience 📔🧠

This is a graduate-level course in neuroscience offered by the Biomedical Engineering group at Sharif University of Technology and taught by Professor Ali Ghazizadeh. The course is designed for students who have already completed a basic course in neuroscience and are interested in exploring advanced topics in the field. Throughout the course, students will delve deeper into topics such as neural coding, perception, and behavior, gaining a more comprehensive understanding of the inner workings of the brain.

Course Topics📃

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Week 1 and 2 : Neural Code

During the first week of the course, we will explore the process by which information is represented and transmitted by neurons in the brain, known as neural coding. We will focus on how the presence of noise in neural circuits affects the encoding and processing of information, and how cortical circuits organize themselves to minimize the impact of noise.

Readings:

• Noise, neural codes and cortical organization by Michael N Shadlen and William T Newsome

• Is there a signal in the noise? by Michael N Shadlen and William T Newsome

• The Highly Irregular Firing of Cortical Cells Is Inconsistent with Temporal Integration of Random EPSPs

• Simple codes versus efficient codes by William R Softky

• Temporal Complexity and Heterogeneity of Single-Neuron Activity in Premotor and Motor Cortex by Mark M.Churchland and Krishna V. Shenoy

• Neural population dynamics during reaching by Mark M. Churchland John P. Cunningham by Mark M. Churchland, John P. Cunningham

• Structure in neural population recordings: an expected byproduct of simpler phenomena? by Gamaleldin F Elsayed & John P Cunningham

• Dimensionality reduction for large-scale neural recordings by John P Cunningham & Byron M Yu

Readings: A Jupiter notebook that contains simulations and answers to questions

These simulations contain useful information about this week's key concepts.

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Week 3: Noise Correlation

During the third week of the course, we will examine the phenomenon of noise correlation in neural circuits, where the activity of two or more neurons is correlated due to shared inputs or connectivity. We will explore the implications of noise correlation for neural coding and information processing, and discuss methods for measuring and manipulating noise correlation.

Readings:

• Stimulus onset quenches neural variability: a widespread cortical phenomenon by Mark M Churchland and Byron M Yu

• Neural correlations, population coding and computation : Bruno B. Averbeck*, Peter E. Latham

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Week 4: Causal Manipulation

During the fourth week of the course, we will explore methods for manipulating neural activity to establish causal relationships between brain activity and behavior. We will discuss the strengths and limitations of different methods, such as optogenetics and pharmacology, and examine the ethical implications of manipulating brain activity.

Readings:

• Millisecond-timescale, genetically targeted optical control of neural activity

• Transcranial Magnetic Stimulation: A Primer by Mark Hallett

• A history of optogenetics: the development of tools for controlling brain circuits with light Edward S. Boyden

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Week 5: Travelling Wave

During the fifth week of the course, we will examine the concept of travelling waves in the brain, where patterns of neural activity propagate across the cortex. We will explore the functional significance of travelling waves and their relationship to perception and behavior.

Readings:

• Propagating waves mediate information transfer in the motor cortex by Doug Rubino, Kay A Robbins & Nicholas G Hatsopoulos

• The stimulus-evoked population response in visual cortex of awake monkey is a propagating wave Lyle Muller, Alexandre Reynaud

• Cortical travelling waves: mechanisms and computational principles by Lyle Muller, Frédéric Chavane

• Theta and alpha oscillations are traveling waves in the human neocortex by Honghui Zhang, Andrew J. Watrous

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Week 6: Motivation and Reward

During the sixth week of the course, we will explore the neural mechanisms underlying motivation and reward, and how they influence behavior. We will discuss the roles of dopamine and other neuromodulators in reward processing, and examine the neural circuits that mediate motivated behavior.

Readings:

• Motivation concepts in behavioral neuroscience by Kent C. Berridge

• Uncertainty and Learning by Peter Dayan Angela J Yu

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Week 7: Reinforcement Learning

During the seventh week of the course, we will examine the concept of reinforcement learning and its neural basis. We will explore how reinforcement learning is used to model behavior and how it is related to reward processing and motivation.

Readings:

• Reward, Motivation, Review and Reinforcement Learning by Peter Dayan and Bernard W. Balleine

• Reinforcement learning: The Good, The Bad and The Ugly by Peter Dayana and Yael Niv

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Week 8: Evidence Accumulation

During the eighth week of the course, we will explore the process by which the brain accumulates evidence over time to make decisions. We will discuss the neural circuits involved in evidence accumulation and how they are related to perception and attention.

Readings:

• Decision Making as a Window on Cognition by Michael N. Shadlen and Roozbeh Kiani

• Representation of Confidence Associated with a Decision by Neurons in the Parietal Cortex by Roozbeh Kiani and Michael N. Shadlen

• Motion perception: Seeing and deciding by MICHAEL N. SHADLEN AND WILLIAM T. NEWSOMEt

• Probabilistic reasoning by neurons by Tianming Yang1 & Michael N. Shadlen1

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Week 9: Visual Search

During the ninth week of the course, we will examine the neural mechanisms underlying visual search, where the brain selectively attends to one or more objects in a complex visual scene. We will discuss how attention is directed in the brain and how it is related to perception and decision-making.

Readings:

• COMPUTATIONAL MODELLING OF VISUAL ATTENTION by Laurent Itti and Christof Koch

• Attentional Selection and the Representation of Stimulus Dimensions by Sabine Kastner and Earl K. Miller

• Visual Search by Jeremy M Wolfe

• Five factors that guide attention in visual search by Jeremy M. Wolfe1 and Todd S. Horowitz

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Week 10: Visual Processing

During the final week of the course, we will explore the neural mechanisms underlying visual processing, including how the brain encodes visual features and how it combines them to form a coherent percept. We will discuss how these mechanisms are related to perception and how they are influenced by attention and other cognitive processes.

Readings:

• Matching Categorical Object Representations in Inferior Temporal Cortex of Man and Monkey by Nikolaus Kriegeskorte, Marieke Mur

• Sparse coding of sensory inputs by Bruno A Olshausen and David J Field

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Assignments

Throughout the course, you will be required to read and critically evaluate the assigned papers, as well as complete written assignments and participate in class discussions. Assignments will be graded based on their quality and thoroughness, as well as your participation in class discussions.