The science of dreams
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The Science of Dreams. Presentation by Charles Beaman MD/PhD Student UT Health. Are Dreams Important?. 2 Nobel Prizes. Neils Bohr Structure of Atoms and Quantum Mechanics. Otto Loewi Chemical Transmission of Nerve Impulses. How Do We Measure Dreams?. How Do We Measure Dreams?.

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The science of dreams

The Science of Dreams



Charles Beaman

MD/PhD Student

UT Health

Are dreams important
Are Dreams Important?

2 Nobel Prizes

  • Neils Bohr

  • Structure of Atoms and Quantum Mechanics

  • Otto Loewi

  • Chemical Transmission of Nerve Impulses

How do we measure dreams1
How Do We Measure Dreams?

Stages of Sleep

Two types of dreams
Two Types of Dreams


Stages of Sleep


Dreaming in rats
Dreaming in Rats

Now we can actually LISTEN to the Neurons in the brain

Nrem dreaming
NREM Dreaming

  • Compressed in Time Scale (1 sec of dream equals 10 of reality)

  • Practice Learned skills

REM Dreaming

  • Expanded Time Scale

  • Simulations?

  • Testing Future Possibilities


  • Intractable Epilepsy Patients

  • Patients in the Hospital for about 1 week

  • We can use this time window to study Sleep

Neural decoding of visual imagery during sleep

Neural Decoding of Visual Imagery During Sleep

T. Horikawa, M. Tamaki, Y. Miyawaki, Y. Kamitani

ATR Computational Neuroscience Laboratories, Kyoto, Japan

Task design
Task Design

Awoken every 5-6 minutes

Outline of sleep nap experiment
Outline of Sleep (Nap) Experiment

  • 3 subjects

  • 1 pm to 5:30 pm

  • fMRI scans + EEG, EOG, EMG, and ECG

  • Usually last 90 minutes over 7 days  > 200 awakenings with visual report

  • Subject awakened after single epoch of alpha-wave suppression and theta-wave (ripple) occurrence (Stage 1 sleep)

Success with awakening at appropriate time
Success with Awakening at Appropriate Time

235 awakenings

198 awakenings

186 awakenings

Example of verbal reports
Example of Verbal Reports

Reports lasted 34 +- 19 seconds

They also collected a “Vividness” and subjective timing of each event, but did not use this data

Non-visual reports were classified as: thought (active thinking), forgot, non-visual, and no report

Visual content labeling wordnet
Visual Content Labeling - WordNet

Based on Synonymy – 117,000 “synsets” that are sets of related words

They assigned all reports to synsets.

Base synsets common specific
Base Synsets – Common, specific

semantically exclusive and specific

Visual stimulus experiment
Visual Stimulus Experiment

  • Used ImageNet – 240 images per base synset

  • Placed in center of screen, subjects freely viewed images without fixation

  • fMRI recorded for each base synset

  • 9 second stimulus block, 6 images sampled from one synset, .75 s with .75 s interleaved blanks

  • Followed by 6 s rest period

  • ~40 blocks per base synset were recorded

Area of brain studied
Area of Brain Studied

  • Higher Visual Cortex – ventral region covering lateral occipital complex, fusiform face area, and parahippocampal area (1000 voxels)

  • Lower Visual Cortex – V1 to V3 (1000 voxels)

  • Subareas (400 voxels)

Pairwise decoding
Pairwise Decoding

Binary classifier was first trained on fMRI data to 2 base synsets, then tested on sleep samples

Containing exclusively 1 of the 2 synsets

Multilabel decoding
Multilabel Decoding