One of the grand challenges in neuroscience is to understand the developing brain ‘in action and in context’ in complex natural settings. To address this challenge, it is imperative to acquire brain data from freely-behaving children to assay the variability and individuality of neural patterns across gender and age.

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Recent advances in scalp electroencephalography (EEG) as a neuroimaging tool have now allowed researchers to overcome technical challenges and movement restrictions typical in traditional neuroimaging studies.  Fortunately, recent mobile EEG devices have enabled studies involving cognition and motor control in natural environments that require mobility, such as during art perception and production in a museum setting, and during locomotion tasks.

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This dataset is associated with the paper, Jackson & Hall 2016, which is open source, and can be found here: http://ieeexplore.ieee.org/document/7742994/

The DataPort Repository contains the data used primarily for generating Figure 1.

Instructions: 

** Please note that this is under construction, and all data and code is still being uploaded whilst this notice is present. Thank-you. Tom **

All code is hosted as a GIT repository (below), as well as instructions, which can be found by clicking on the link/file called README.md in that repository.

https://github.com/thomasmhall-newcastle/IEEE-TNSRE-2016-lfLFPs

You are free to clone/pull this repository and use it under MIT license, on the understanding that any use of this code will be acknowledged by citing the original paper, DOI: 10.1109/TNSRE.2016.2612001, which is Open Access and can be found here: http://ieeexplore.ieee.org/document/7742994/

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The data set collected using a Cerebus neural signal acquisition equipment involed thirteen odor stimulating materials, five of which (smelling like rose (A), caramel (B), rotten (C), canned peach (D), and excrement (E)) were selected from the T&T olfactometer (from the Daiichi Yakuhin Sangyo Co., Ltd., Japan) and the remaining eight from essential oils (i.e., mint (F), tea tree (G), coffee (H), rosemary (I), jasmine (J), lemon (K), vanilla (L) and lavender (M)).

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The data set collected using a Cerebus neural signal acquisition equipment involved 2 types of odors (smelling like roses and rotten odors), each with 5 concentrations. Five concentrations of the rose odor are expressed as A10-3.0 (A30), A10-3.5 (A35), A10-4.0 (A40), A10-4.5 (A45) and A10-5.0 (A50), and five concentrations of the rotten odor are expressed as C10-4.0 (C40), C10-4.5 (C45), C10-5.0 (C50), C10-5.5 (C55) and C10-6.0 (C60).

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Abstract— Objective: Recently, pupil oscillation synchronized with a steady visual stimulus was employed for an input of an interface. The system is inspired by steady-state visual evoked potential (SSVEP) BCIs, but it eliminates the need for contact with the participant because it does not need electrodes to measure electroencephalography. However, the stimulation frequency is restricted to being below 2.5 Hz because of the mechanics of pupillary vibration and information transfer rate (ITR) is lower than SSVEP BCIs.

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EEG consists of collecting information from brain activity in the form of electrical voltage. Epileptic Seizure prediction and detection is a major sought after research nowadays. This dataset contains data from 11 patients of whom seizures are observed in EEG for 2 patients.

 

The total duration of seizures is 170 seconds. The number of channels is 16 and data is collected at 256Hz sampling rate.

 

The final dataset files in .csv format contain 87040 rows x 17 columns,

 

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756 Views

Brainwave entrainment beats detection has become an important topic due to the ability of these beats to change human brain waves to decrease anxiety, help focus attention, improve memory, improve mood, enhance creativity, reduce pain, help with meditation, enhance mental flexibility, and enhance sleep quality. However, listening to it can cause unwanted side effects as it can increase feelings of depression, anxiety, anger, and confusion in some people.

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135 Views

Brainwave entrainment beats detection has become an important topic due to the ability of these beats to change human brain waves to decrease anxiety, help focus attention, improve memory, improve mood, enhance creativity, reduce pain, help with meditation, enhance mental flexibility, and enhance sleep quality. However, listening to it can cause unwanted side effects as it can increase feelings of depression, anxiety, anger, and confusion in some people.

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257 Views

This dataset contains 10 well-segmented 2D human brain numerical phantoms. And they are transformed from MRA imaging modality, which could be used for photoacousing imaging research and the related learning tasks.

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463 Views

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