QEEG phenotypes, depression and TMS

Natalia Hackett

doi:10.1002/pnp.510

QEEG phenotypes, depression and TMS

Natalia Hackett^*

^*Corresponding author for this work

Bristol Medical School

Research output: Contribution to journal › Article (Academic Journal) › peer-review

4 Citations (Scopus)

Abstract

In 2017, depression became recognised as the leading cause of ill health and disability worldwide.¹ In England, 1 in 6 people experience mental health problems every week,² 75%³ of whom may not be able to access the treatment they need. There is a growing interest in electroencephalogram (EEG) analysis to identify anomalous patterns of electrical activity in the brains of depressed patients. These patterns are known as EEG phenotypes.

Original language	English
Pages (from-to)	23-26
Number of pages	4
Journal	Progress in Neurology and Psychiatry
Volume	22
Issue number	3
Early online date	22 Aug 2018
DOIs	https://doi.org/10.1002/pnp.510
Publication status	Published - Aug 2018

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title = "QEEG phenotypes, depression and TMS",

abstract = "In 2017, depression became recognised as the leading cause of ill health and disability worldwide.1 In England, 1 in 6 people experience mental health problems every week,2 75%3 of whom may not be able to access the treatment they need. There is a growing interest in electroencephalogram (EEG) analysis to identify anomalous patterns of electrical activity in the brains of depressed patients. These patterns are known as EEG phenotypes.",

author = "Natalia Hackett",

year = "2018",

month = aug,

doi = "10.1002/pnp.510",

language = "English",

volume = "22",

pages = "23--26",

journal = "Progress in Neurology and Psychiatry",

issn = "1367-7543",

publisher = "Wiley",

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TY - JOUR

T1 - QEEG phenotypes, depression and TMS

AU - Hackett, Natalia

PY - 2018/8

Y1 - 2018/8

N2 - In 2017, depression became recognised as the leading cause of ill health and disability worldwide.1 In England, 1 in 6 people experience mental health problems every week,2 75%3 of whom may not be able to access the treatment they need. There is a growing interest in electroencephalogram (EEG) analysis to identify anomalous patterns of electrical activity in the brains of depressed patients. These patterns are known as EEG phenotypes.

AB - In 2017, depression became recognised as the leading cause of ill health and disability worldwide.1 In England, 1 in 6 people experience mental health problems every week,2 75%3 of whom may not be able to access the treatment they need. There is a growing interest in electroencephalogram (EEG) analysis to identify anomalous patterns of electrical activity in the brains of depressed patients. These patterns are known as EEG phenotypes.

UR - http://www.scopus.com/inward/record.url?scp=85052054322&partnerID=8YFLogxK

U2 - 10.1002/pnp.510

DO - 10.1002/pnp.510

M3 - Article (Academic Journal)

AN - SCOPUS:85052054322

VL - 22

SP - 23

EP - 26

JO - Progress in Neurology and Psychiatry

JF - Progress in Neurology and Psychiatry

SN - 1367-7543

IS - 3

ER -

QEEG phenotypes, depression and TMS

Abstract

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