Spring 2027

Behavioral Neuroscience

Behavioral Neuroscience covers the biological basis of human and animal behaviors, including perception, action, cognition, social interaction, and disease, using weekly themes to explore neural mechanisms.

offering recorded3–4 credits
Recorded instructors · Spring 2027 Yuri Saalmann4.0/5

Summary

1 / 6

Past student reviews · Yuri Saalmann

The course was based on three multiple-choice exams drawn from slides, and one student expected lots of information to memorize.

What you’ll be able to do

  • Describe how neurons code information.

  • Characterize how the brain is organized at the cellular, circuit and systems levels.

  • Interpret plots of neural activity.

  • Explain neural mechanisms which enable us to perceive and navigate our environment.

  • Explain neural mechanisms which enable cognition and memory.

  • Explain neural mechanisms which enable us to interact with others.

Source: UW Guide

Grade history

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average GPA
letter grades
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All recorded terms · compare terms & instructors

Prerequisites

Course map

PSYCH 202, (ZOOLOGY/​BIOLOGY 101 and 102),ZOOLOGY/​BIOLOGY/​BOTANY 151, or (BIOCORE 381 and 382)

PSYCH 454 used by

“Used by” includes alternatives; linked courses may have other requirements. This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree

Professors

Spring 2027

Yuri Saalmann

Adjusted rating
RMP difficulty
captured reviews
About this rating

Raw average: 4.16/5 from 51 quality ratings. The adjusted rating blends this with the UW review average (3.66/5), weighted as 20 additional ratings. Smaller samples stay closer to that average. Each captured review is counted once in the prior; this does not correct who chooses to leave a review.

For this course: 4.2/5 raw quality · 3.2/5 difficulty · 29 reviews

RMP profile ↗ · All captured review dates; profile matched by name.

Past student reviews · Yuri Saalmann

Yuri Saalmann taught this course as three multiple-choice exams, each worth 33% of the grade. Students found the lectures dense with a lot of information to memorize, but noted he was clear about exam content and provided summary slides and recordings.

While some found the lectures fascinating and easy to digest, others felt the pacing was disorganized due to the volume of material covered in 75-minute sessions. Overall, students described the exams as fair provided they studied the slides thoroughly.

Recent recorded grades — Spring 2024: 3.08 GPA, 48.2% A/AB (n=417 letter grades); Spring 2025: 3.50 GPA, 72.0% A/AB (n=429 letter grades); Spring 2026: 3.09 GPA, 50.1% A/AB (n=451 letter grades). Includes jointly taught sections.

Historical instructors & teaching patterns

Past student reviews · Catherine Auger

Past students of Catherine Auger reported mixed experiences, with some finding her lectures interesting and humorous, while others criticized her for unclear teaching, unorganized slides, and unresponsive emails. Several reviewers described exams as difficult, poorly representative of the material, and subject to picky grading. Students noted that reading the textbook was essential for success, and opinions on her ability to answer questions varied significantly.

CATHERINE AUGER is recorded teaching in Spring 2008, Spring 2009, Spring 2010, Spring 2013. Recorded history may be incomplete and does not establish a future schedule.

YURI SAALMANN is recorded teaching in Fall 2014, Fall 2015, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2022, Spring 2023, Spring 2024, Spring 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

Recorded history may be incomplete and does not establish a future schedule.

Calendar & sections

Spring 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction0 / 4550
LEC 002Classroom Instruction0 / 250
DIS 301Classroom Instruction0 / 250

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.

Meeting source records
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Student experience

the class

Past student reviews · Yuri Saalmann

Yuri Saalmann taught the material as fascinating, and one student found his explanations made concepts easy to digest.

Recent recorded grades — Spring 2024: 3.08 GPA, 48.2% A/AB (n=417 letter grades); Spring 2025: 3.50 GPA, 72.0% A/AB (n=429 letter grades); Spring 2026: 3.09 GPA, 50.1% A/AB (n=451 letter grades).

difficulty & workload

Past student reviews · Yuri Saalmann

The course was based on three multiple-choice exams drawn from slides, and one student expected lots of information to memorize.

Past student reviews · Yuri Saalmann

One student found Yuri fun but easy to tune out, and said last-minute cramming did not work.

Topics

  • Biological basis of human and animal behaviors, including perception, action, cognition, social interaction, and disease.
  • Brain organization at cellular, circuit, and systems levels.
  • How neurons code information.

Skills

  • Describing neuronal coding and characterizing brain organization at cellular, circuit, and systems levels.
  • Explaining neural mechanisms for perception, navigation, cognition, memory, and social interaction.

Grades

Historical instructor

Spring 2027 · Projected

Before grades are released

– average GPA

Approximate 80% prediction interval

About this estimate

The course’s semester-average GPA, not an individual student’s grade. The center uses 5 same-season terms, weighted toward recent results.

The range uses the finite-sample 80th-percentile rank of absolute errors from earlier same-season forecasts. Each forecast uses only records from earlier terms. At least four forecasts are required; bounds are rounded outward and limited to 0–4. This is an empirical estimate: changing instructors or grading policies can reduce its coverage.

8 earlier forecasts · 0.20 GPA average error.

Grades over time

Through Spring 2027

More grade details Grade mix, volume & source data

Where this course fits relative to

Latest available grades · Spring 2026 · all course levels

GPA

Higher than % of other courses in this group.

Course GPAs · red marks this course’s range

letter grades

More recorded grades than % of other courses in this group.

Typical course in this group: letter grades.

About this comparison

1280 courses over the same term, each with at least 30 recorded letter grades. Cross-listed courses count once. GPA is not a measure of difficulty or teaching quality. The typical course is the median by recorded grade count; tied values are not counted as lower. Grade counts describe course scale, not unique students or typical section size.

Descriptions compare GPA with this group’s average: at least 0.20 higher or lower; otherwise close to average. Section size uses median recorded enrollment: small up to 30, mid-sized 31–99, large 100+. Lectures and discussion/lab sections are described separately.

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

Catalog observation history

Observations at scan time; dates do not imply when a catalog change took effect.

Download part 1
Selected offering source records
PSYCH 454 · Spring 2027

Behavioral Neuroscience

Recorded 2026-10-29
Raw records 
[
  {
    "run_id": "20261029T213040-0fa85c20",
    "semester": "1274",
    "observed_at": "2026-10-29 21:30:40.248904+00:00",
    "offering_id": "1274:820:016406",
    "course_id": "PSYCH 454",
    "course_uid": "course_0593d58e1f8ad103506a6dfe",
    "term_id": "1274",
    "source_course_id": "016406",
    "source_subject_id": "820",
    "title": "Behavioral Neuroscience",
    "credits_min": 3,
    "credits_max": 4,
    "typically_offered": "Fall, Spring, Summer"
  }
]
Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

Read original reviews
Download part 1
Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
Dataset & model

Recorded 2026-10-29

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1Download part 2
Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "d82ba73c10518339015993a04c825c4acdf650aa6d46e57561e4803b52880901",
  "requirements_status": "valid",
  "dataset_revision": "c9cd06eaa45f9ddf7e69faa38b89ff3d3dd995dd",
  "observed_at": "2026-10-29 21:30:40.248904+00:00"
}