Avishek Adhikari
Department of Neuroscience
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4.0
Overall Rating
Based on 1 User
Easiness 5.0 / 5 How easy the class is, 1 being extremely difficult and 5 being easy peasy.
Clarity 5.0 / 5 How clear the class is, 1 being extremely unclear and 5 being very clear.
Workload 5.0 / 5 How much workload the class is, 1 being extremely heavy and 5 being extremely light.
Helpfulness 5.0 / 5 How helpful the class is, 1 being not helpful at all and 5 being extremely helpful.

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GRADE DISTRIBUTIONS
17.0%
14.1%
11.3%
8.5%
5.7%
2.8%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

26.0%
21.7%
17.3%
13.0%
8.7%
4.3%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

33.3%
27.8%
22.2%
16.7%
11.1%
5.6%
0.0%
A+
A
A-
B+
B
B-
C+
C
C-
D+
D
D-
F

Grade distributions are collected using data from the UCLA Registrar’s Office.

ENROLLMENT DISTRIBUTIONS
Clear marks

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Reviews (1)

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Quarter: Spring 2022
Grade: A+
Verified Reviewer This user is a verified UCLA student/alum.
June 20, 2022

This class is cakewalk compared to the other two in the series. The professors for this course are Wassum, Adhikari, and Suthana (in that order).

Wassum's module is all about motivation - why we do what we do. And she explores this topic through hunger and reward-seeking behaviors which she maps to brain circuitry from a buttload of mice/rat experiments. All of her slides are just figures of graphs and a lot of them say the same in thing in different ways, which is core part of behavioral neuroscience - converging evidence is IMPORTANT!

Adhikari is hands-down the BEST neuroscience professor in the department. He cracks jokes so frequently it sometimes feels you're watching a stand-up comedian, rather than a lecture, which makes it super engaging. His module covers long-term potentiation and depression (LTP/LTD), a lot of stuff on memory (Patient H.M.), you dive into the circuitry and cell types of the hippocampus (trisynaptic circuit, place cells, etc.) - and again all of this is through many, many experiments that have been done on rats.

Suthana is also a really sweet professor (she was an undergrad here and did her PhD here, as well) and her module is on cognitive neuroscience. You go through all the different techniques used in Cog Neuro, like fMRI, EEGs, single-neuron electrodes, etc. And you learn about experiments using each of these, and their pros and cons. I found this one the least interesting, because it was too computational for my liking at times, but that's what CogNeuro is all about and it was cool to see a different side of neuroscience than previously seen.

The class is structured as such:
- 75% Exams (25% each module) - each exam is 30 MC with 1-2 bonus points. They also give practice MC questions that are very similar if not the same prior to the exam (this was nice because 101A/B didn't do that)
- 20% Weekly Write-Ups - you have a research paper assigned each week to write about in a creative way (this can be like a blog post, Twitter thread, or press release) and you just summarize the experiments done in the paper and tie it back to lecture that week (lowest TWO are dropped)
- 5% Clinical Correlation - lowest one is dropped so you can just skip one of the two offered.

It's SUPER easy to do well in this class, the test are fair, there's EC, and it's overall such a confidence boost, if you're like me and didn't do so hot in 101B.

Helpful?

1 0 Please log in to provide feedback.
Verified Reviewer This user is a verified UCLA student/alum.
Quarter: Spring 2022
Grade: A+
June 20, 2022

This class is cakewalk compared to the other two in the series. The professors for this course are Wassum, Adhikari, and Suthana (in that order).

Wassum's module is all about motivation - why we do what we do. And she explores this topic through hunger and reward-seeking behaviors which she maps to brain circuitry from a buttload of mice/rat experiments. All of her slides are just figures of graphs and a lot of them say the same in thing in different ways, which is core part of behavioral neuroscience - converging evidence is IMPORTANT!

Adhikari is hands-down the BEST neuroscience professor in the department. He cracks jokes so frequently it sometimes feels you're watching a stand-up comedian, rather than a lecture, which makes it super engaging. His module covers long-term potentiation and depression (LTP/LTD), a lot of stuff on memory (Patient H.M.), you dive into the circuitry and cell types of the hippocampus (trisynaptic circuit, place cells, etc.) - and again all of this is through many, many experiments that have been done on rats.

Suthana is also a really sweet professor (she was an undergrad here and did her PhD here, as well) and her module is on cognitive neuroscience. You go through all the different techniques used in Cog Neuro, like fMRI, EEGs, single-neuron electrodes, etc. And you learn about experiments using each of these, and their pros and cons. I found this one the least interesting, because it was too computational for my liking at times, but that's what CogNeuro is all about and it was cool to see a different side of neuroscience than previously seen.

The class is structured as such:
- 75% Exams (25% each module) - each exam is 30 MC with 1-2 bonus points. They also give practice MC questions that are very similar if not the same prior to the exam (this was nice because 101A/B didn't do that)
- 20% Weekly Write-Ups - you have a research paper assigned each week to write about in a creative way (this can be like a blog post, Twitter thread, or press release) and you just summarize the experiments done in the paper and tie it back to lecture that week (lowest TWO are dropped)
- 5% Clinical Correlation - lowest one is dropped so you can just skip one of the two offered.

It's SUPER easy to do well in this class, the test are fair, there's EC, and it's overall such a confidence boost, if you're like me and didn't do so hot in 101B.

Helpful?

1 0 Please log in to provide feedback.
1 of 1
4.0
Overall Rating
Based on 1 User
Easiness 5.0 / 5 How easy the class is, 1 being extremely difficult and 5 being easy peasy.
Clarity 5.0 / 5 How clear the class is, 1 being extremely unclear and 5 being very clear.
Workload 5.0 / 5 How much workload the class is, 1 being extremely heavy and 5 being extremely light.
Helpfulness 5.0 / 5 How helpful the class is, 1 being not helpful at all and 5 being extremely helpful.

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There are no relevant tags for this professor yet.

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