Presentation(lokesh)

REVIEW OF RESEARCH PAPERS
NAME : LOKESH AGRAWAL
SEMESTER : 8th
CCTID : 9034

PROJECT TITLE :
To study of “ Resting-state functional connectivity pattern of regional
interactions & spontaneous fluctuations in brain in Anxiety and Depression
conditions.”

 Anxiety :-
 Feelings of unease, worry, tension, and stress can be defined as anxiety, usually
generalized and unfocused as an overreaction to a situation that is only subjectively seen
as menacing.
 Or can be defined as an unpleasant state of mental uneasiness or concern that causes
physical and psychological discomfort. Extreme anxiety disrupts and unsettles behavior by
lowering the individual's concentration and affecting their muscular control.
 It is often accompanied by restlessness, fatigue, problems in concentration, and muscular
tension. Anxiety is not considered to be a normal reaction to a perceived stressor although
many feel it occasionally.

Types of anxiety :-
Trait anxiety
Trait anxiety refers to a general level of stress that is characteristic of an individual,
that is, a trait related to personality. Trait anxiety varies according to how individuals
have conditioned themselves to respond to and manage the stress.
State anxiety
State anxiety is characterized by a state of heightened emotions that develop in
response to a fear or danger of a particular situation. State anxiety can contribute to a
degree of physical and mental paralysis, preventing performance of a task or where
performance is severely affected, such as forgetting movements during a dance or
gymnastic routine; to breaking in sprint or swim starts or missing relatively easy shots at
goal i.e. pressure situations.
Depression is a state of low mood and aversion to activity that can affect a person's
thoughts, behaviour, feelings and sense of well-being.Depressed people can feel sad,
anxious, empty, hopeless, worried, helpless, worthless, guilty, irritable, hurt, or restless.
Loss of interest in or pleasure from most daily activities.

 Difference b/w Anxiety and Depression :-
 Anxiety Disorders
 Anxiety Disorders are characterized by a sense of doubt and vulnerability about future events.
 The attention of anxious people is focused on their future prospects, and the fear that those future
prospects will be bad.
 Anxiety Disorders are characterized by a variety of symptoms involving anxious thoughts,
unexplained physical sensations, and avoidant or self protective behaviours.
 Depression
 A person whose primary problem is depression, rather than anxiety, generally doesn't show the
same fear and uncertainty that people do with anxiety disorders.
 Depressed people are not so preoccupied with worrying about what might happen to them in the
future. They think they already know what will happen, and they believe it will be bad, the same
bad stuff that's happening to them now.
 The key symptoms of depression include:
 * Feeling sad, and/or hopeless
* Lack of interest and enjoyment in activities that used to be fun and interesting
* Physical aches and pains without physical cause; lack of energy
* Difficulty concentrating, remembering, and/or making decisions
* Changes in appetite and weight
* Unwelcome changes in usual sleep pattern
* Thoughts of death and suicide
 Depression may come on as a relatively sudden and severe problem,
 or it may consist of a longer term set of symptoms which are less severe.

 Signs and symptoms of anxiety disorders
 Characterized by excessive, uncontrollable and often irrational worry about
everyday things that is disproportionate to the actual source of worry, it is
diagnosed as generalized anxiety disorder (GAD).
 Subtypes of anxiety disorders are phobias, social anxiety, obsessive-
compulsive behavior, and Posttraumatic stress disorder.
 The physical effects of anxiety may include heart
palpitations, tachycardia, muscle weakness and tension, fatigue, nausea, chest
pain, shortness of breath, headache, stomach aches, or tension headaches.
 External signs of anxiety may include pallor, sweating, trembling, and papillary
dilation.
 As the body prepares to deal with a threat, blood pressure, heart rate,
perspiration, blood flow to the major muscle groups are increased,
while immune and digestive functions are inhibited.
 Neural circuitry involving the amygdala and hippocampus is thought to
underlie anxiety.
 Research is under-way to unravel possible molecular mechanisms underlying
anxiety and comorbid conditions. One candidate gene with polymorphisms that
influence anxiety is PLXNA2.
 Caffeine may cause or exacerbate anxiety disorders.

INDEX :
 RESEARCH PAPER 1st…...............................................................................................................................
 PAPER TITLE
 KEY WORDS
 ABSTRACT
 METHODOLOGY
 CONCLUSION
 REFERENCES
 RESEARCH PAPER 2nd………………………………………………………………………………………………….
 PAPER TITLE
 KEY WORDS
 ABSTRACT
 METHODOLOGY
 CONCLUSION
 REFERENCES
 RESEARCH PAPER 3rd………………………………………………………………………………………………......
 PAPER TITLE
 KEY WORDS

 ABSTRACT
 METHODOLOGY
 CONCLUSION
 REFERENCES
 RESEARCH PAPER 4th…………………………………………………………………………………………………..
 PAPER TITLE
 KEY WORDS
 ABSTRACT
 METHODOLOGY
 CONCLUSION
 REFERENCES
 RESEARCH PAPER 5th…………………………………………………………………………………………………..
 PAPER TITLE
 KEY WORDS
 ABSTRACT
 METHODOLOGY
 CONCLUSION
 REFERENCES

RESEARCH PAPER 1st
TITLE : “Altered Effective Connectivity Network of the Amygdala
in Social Anxiety Disorder: A Resting-State fMRI Study”.
KEY WORDS :
Anxiety ; Depression ; Rest State FMRI; Connectivity Network
,Independent component analysis.
ABSTRACT :The amygdala is often found to be abnormally recruited in social
anxiety disorder (SAD) patients. The question whether amygdala activation is primarily
abnormal and affects other brain systems or whether it responds‘‘normally’’ to an
abnormal pattern of information conveyed by other brain structures remained
unanswered. we investigated a network of effective connectivity associated with the
amygdala using Granger causality analysis on resting-state functional MRI data of 22
SAD patients and 21 healthy controls (HC). Implications of abnormal effective
connectivity and clinical
severity were investigated using the Liebowitz Social Anxiety Scale (LSAS).
Decreased influence from inferior temporal gyrus (ITG) to amygdala was found in
SAD, while bidirectional influences between amygdala and visual cortices were
increased compared to HCs. Clinical relevance of decreased effective connectivity

 from ITG to amygdala was suggested by a negative correlation of LSAS avoidance
scores and the value of Granger causality.The amygdala is placed in a central position of
dysfunction characterized both by decreased regulatory influence of orbitofrontal cortex
and increased crosstalk with visual cortex.
 METHODOLOGY: Diagnosis of SAD was determined by consensus between the two
attending psychiatrists and a trained interviewer using the Structured Clinical Interview
DSM-IV (SCID)-Patients Version.
 Subjects were excluded from the sample who presented any other psychiatric disorder
according to structured clinical interview for DSM-IV Axis-I.
 Additionally, we excluded subjects who presented with a general medical condition. SAD
patients were not under psychotherapy or psychiatric medications at the moment of the
study, however, all patients underwent the psychotherapy and some of them underwent
psychiatric medications after the study.
 The second group was composed of 22 age-, sex-, education matched healthy
controls (HC) (all right-handed) who were recruited and screened using the SCID-
Patients Version to confirm the current absence of psychiatric and neurological illness.
Additionally, healthy controls were interviewed to confirm that there was no history of
psychiatric illness among their firstdegree relatives.
 Brain MR imaging (i.e. T1-weighted images) was inspected by an experienced
neuroradiologist, and no gross abnormalities were observed in either group.
 All participants of the two groups were evaluated with the Spielberger State-Trait
Anxiety Inventory (STAI-Y), Hamilton Anxiety Rating Scale (HAMA), Hamilton
Depression Rating Scale (HAMD) and Liebowitz Social Anxiety Scale (LSAS). LSAS
is one of the most widely used scale in SAD assessment.

CONCLUSION :
 We found significantly altered effective connectivity
between the amygdala and temporal as well as
prefrontal cortices, main effects are presented here, for a
complete description of the areas showing an altered
effective connectivity from or to the amygdala.
 Psychological Data or Behavioral Data :Compared with
HCs, SAD patients showed significantly higher scores on
the LSAS (including total score, fear factor and avoidance
factor) assessment social anxiety symptom scales, and
higher scores on the HAMD and HAMA, and higher levels
of anxiety as assessed by the STAI-T and prescanning
STAI-S.

Figure 1. Altered effective connectivity from the amygdala. Altered effective connectivity from the
left amygdala (A) and from the right amygdala (B) to other brain regions (Pv0:05, FDR corrected)
when SAD compared to HC. The hot and cold colors indicate the brain regions that
show significantly increased and decreased effective connectivity, respectively. The color scale
represents T values.
Effective Connectivity from the Left Amygdala :
Compared to HC, SAD patients showed significantly increased effective
connectivity from the left amygdala to several brain regions which included
the middle frontal cortex, temporal cortex, somato-motor and visual
cortex and the cerebellum , Furthermore, decreased effective connectivity
was found from the left amygdala to the left superior frontal gyrus (medial),
and right middle temporal gyrus and the bilateral postcentral gyri .

 Effective Connectivity from the Right Amygdala :
Compared to HC, SAD patients showed significant increased
effective connectivity from the right amygdala to several brain regions that
included the medial orbitofrontal gyrus (mOFG), temporal, occipital and
limbic/paralimbic cortex (parahippocampus and hippocampus) (Fig.
1B). The results further revealed decreased effective connectivity from
the right amygdala to the right superior frontal gyrus and hippocampus;
and several regions in parietal lobe. and cerebellum.
Regions showing increased effective connectivity

Figure . Regions showing decreased effective connectivity. Decreased directions are marked
with blue arrows in SAD compared to HC. Scatter plots showed correlations between effective
connectivity in group level regions (see Figures 1 and 2) and avoidance factor in LSAS in SAD
patients (red line and red open circles), and in HCs (blue line and blue solid circles), separately
(Pv0:05). (AMG: amygdala, ITG: inferier temporal gyrus).

 REFERENCES :
 1. Stein MB, Stein DJ (2008) Social anxiety disorder. Lancet 371: 1115–1125.
 2. Freitas-Ferrari MC, Hallak JE, Trzesniak C, Filho AS, Machado-de-Sousa JP, et al. (2010)
Neuroimaging in social anxiety disorder: a systematic review of the literature. Prog
Neuropsychopharmacol Biol Psychiatry 34: 565–580.
 3. Ohayon MM, Schatzberg AF (2010) Social phobia and depression: prevalence and
comorbidity. J Psychosom Res 68: 235–243.
 4. Ferrari MC, Busatto GF, McGuire PK, Crippa JA (2008) Structural magnetic resonance
imaging in anxiety disorders: an update of research findings. Rev Bras Psiquiatr 30: 251–264.
 5. Engel K, Bandelow B, Gruber O, Wedekind D (2009) Neuroimaging in anxiety disorders. J
Neural Transm 116: 703–716.
 6. Phan KL, Fitzgerald DA, Cortese BM, Seraji-Bozorgzad N, Tancer ME, et al. (2005) Anterior
cingulate neurochemistry in social anxiety disorder: 1H-MRS at 4 Tesla. Neuroreport 16: 183–
186.
 7. Simmons A, Matthews SC, Feinstein JS, Hitchcock C, Paulus MP, et al. (2008) Anxiety
vulnerability is associated with altered anterior cingulate response to an affective appraisal task.
Neuroreport 19: 1033–1037.
 8. Guyer AE, Lau JY, McClure-Tone EB, Parrish J, Shiffrin ND, et al. (2008)

RESEARCH PAPER 2ND
 TITLE : “Decreased regional homogeneity in major depression as revealed by
resting-state functional magnetic resonance imaging”.
 KEY WORDS : Depression; First episode; FMRI; Resting state; Regional homogeneity
 ABSTRACT : Functional imaging studies indicate abnormal activities in cortico-
limbic network in depression during either task or resting state. The present work
was to explore the abnormal spontaneous activity shown with regional
homogeneity (ReHo) in depression by resting-state functional magnetic
resonance Imaging(Fmri).
 METHODOLOGY : Using fMRI, the differences of regional brain activity were
measured in resting state in depressed vs. Healthy participants.
 Sixteen participants firstly diagnosed with major depressive disorder and 16 controls
were scanned during resting state. A novel method based on ReHo was used to
detect spontaneous hemodynamic responses across the whole brain.

 PSYCHOMETRIC TEST : BDI(II)Back Depression Inventry.
 ReHo : ReHo analysis was performed for each participant by calculating kendall’s
coefficient of concordance (KCC) of the time series of a given voxel with those of its
nearest neighbors (26 voxels) on a voxel-wise basis .The KCC program was coded in
MATLAB By ReHo analysis, an individual ReHo map was generated. The KCC can be
computed by the following formula:
Where W is the KCC among given voxels, ranging from 0 to 1; Ri is the sum rank of the ith
time point; R ur is the mean of the Ri’s; K is the number of time series within a measured
cluster (K¼27, one given voxel plus the number of its neighbors) and n is the number of
ranks.
 Conclusions :
 Brain areas showed decreased ReHo in depressed patients.
 ReHo in the left thalamus, left temporal lobe, left cerebellar posterior lobe, and
the bilateral occipital lobe was found to be significantly decreased in depression
compared to healthy controls in resting state of depression. Abnormal
spontaneous activity exists in the left thalamus, left temporal lobe, left
cerebellar posterior lobe, and the bilateral occipital lobe. And the ReHo may
be a potential reference in understanding the distinct brain activity in resting state
of depression.

Location of different KCC between depressed patients and controls by TT
coordinates. A: Left thalamus. B: Left temporal lateral lobe. C: Left temporal wall
lobe. D: Left cerebellar posterior lobe. E: Left occipital lobe. F: Right
occipital lobe. Blue signals show lower KCC of depressed patients than controls. Left
column: Transverse section. Middle column: Median sagittal section. Right column:
Coronal section.

 REFERENCES :
 1. Matthews SC, Strigo IA, Simmons AN, Yang TT, Paulus MP. Decreased functional coupling of
the amygdala and supragenual cingulate is related to increased depression in unmedicated
individuals with current major depressive disorder. J Affect Disord 2008; 111: 13-20.
 2. Yao ZJ, Wang L, Lu Q, Liu HY, Teng GJ. Regional homogeneity in depression and its
relationship with separate depressive symptom clusters: a resting-state fMRI study. JAffect
Disord 2009; 115: 430-438.
 3. Yuan Y, Zhang Z, Bai F, Yu H, Shi Y, Qian Y, et al. Abnormal neural activity in the patients with
remitted geriatric depression: A resting-state functional magnetic resonance imaging study. J
Affect Disord 2008; 111: 145-152.
 4. Gusnard DA, Raichle ME. Searching for a baseline: functional imaging and the resting human
brain. Nat Rev Neurosci 2001; 2: 685-694.
 5. Anand A, Li Y, Wang Y, Lowe MJ, Dzemidzic M. Resting state corticolimbic connectivity
abnormalities in unmedicated bipolar disorder and unipolar depression. Psychiatry Res
2009;171: 189-198.
 6. Liu Y, Wang K, Yu C, He Y, Zhou Y, Liang M, et al. Regional homogeneity, functional
onnectivity and imaging markers of Alzheimer’s disease: a review of resting-state fMRI studies.
Neuropsychologia 2008; 46: 1648-1656.

 RESEARCH PAPER 3rd
 TITLE : “Increased Amygdalar and Hippocampal Volumes inYoung Adults
with Social Anxiety ”.
 KEY WORDS : Bold signal , Regional cerebral blood flow ; Parieto-temporal brain
region.
 ABSTRACT : Functional neuroimaging studies have consistently
shown abnormal limbic activation patterns in socially anxious
individuals. This study explored the existence of structural
differences in the whole brain, amygdala, and hippocampus of
subjects with clinical and subthreshold social anxiety compared
to healthy controls. We hypothesized that there would be
volumetric differences across groups, without predicting their
direction (i.e. enlargement or reduction).

 METHODOLOGY : Subjects classified as having social anxiety disorder (n
= 12), subthreshold social anxiety (n = 12) and healthy controls (n =
14) underwent structural magnetic resonance imaging scans. The
amygdala and hippocampus were defined a priori as regions of
interest and volumes were calculated by manual tracing. Whole brain
volume was calculated using voxelbased.
 CONCLUSION : The bilateral amygdala and left hippocampus
were enlarged in socially anxious individuals relative to controls.
The volume of the right hippocampus was enlarged in
subthreshold social anxiety participants relative to controls. No
differences were found across groups in respect to total brain
volume. Our results show amygdalar and hippocampal volume
alterations in social anxiety, possibly associated with symptom
severity.

 REFERENCES :
 Freitas-Ferrari MC, Hallak JE, Trzesniak C, Filho AS, Machado-de-Sousa JP, et al. (2010) Neuroimaging in
social anxiety disorder: a systematic review of the literature. Prog Neuropsychopharmacol Biol Psychiatry 34:
565–580.
 2. Phillips RG, LeDoux JE (1992) Differential contribution of amygdala and hippocampus to cued and
contextual fear conditioning. Behav Neurosci 106: 274–285.
 3. Liao W, Qiu C, Gentili C, Walter M, Pan Z, et al. (2010) Altered effective connectivity network of the
amygdala in social anxiety disorder: a resting-state FMRI study. PLoS One 22: e15238.
 4. Hahn A, Stein P, Windischberger C, Spindelegger C, Moser E, et al. (2011) Reduced resting-state functional
connectivity between amygdala and orbitofrontal cortex in social anxiety disorder. Neuroimage 56: 881–889.
 5. Potts NL, Davidson JR, Krishnan KR, Doraiswamy PM (1994) Magnetic resonance imaging in social phobia.
Psychiatry Res 52: 35–42.
 6. Irle E, Ruhleder M, Lange C, Seidler-Brandler U, Salzer S, et al.(2010) Reduced amygdalar and
hippocampal size in adults with generalized social phobia. J Psychiatry Neurosci 35: 126–131.
 7. Liao W, Xu Q, Mantini D, Ding J, Machado-de-Sousa JP, et al. (2011) Altered gray matter morphometry and
resting-state functional and structural connectivity in social anxiety disorder. Brain Res 4: 167–177.
 8. Syal S, Hattingh CJ, Fouche´ JP, Spottiswoode B, Carey PD, et al. (2012) Gray matter abnormalities in
social anxiety disorder: a pilot study. Metab Brain Dis 27: 299–309.

 RESEARCH PAPER 4th
 TITLE : “Spontaneous fluctuations in brain activity observed with
functional magnetic resonance imaging”.
 KEY WORDS : Bold signal , Regional cerebral blood flow ; Parieto-temporal brain region.
 ABSTRACT : The majority of functional neuroscience studies have focused
on the brain’s response to a task or stimulus.
 However, the brain is very active even in the absence of explicit input or
output.
 Spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal
of functional magnetic resonance imaging as a potentially important and
revealing manifestation of spontaneous neuronal activity. These studies have
provided insight into the intrinsic functional architecture of the brain, variability
in behaviour and potential physiological correlates of neurological and
psychiatric disease.

METHODOLOGY :
Principal : Spontaneous neuronal activity refers to activity that is
not attributable to specific inputs or outputs; it represents neuronal
activity that is intrinsically generated by the brain. As such, fMRI
studies of spontaneous activity attempt to minimize changes in
sensory input and refrain from requiring subjects to make responses
or perform specific cognitive tasks
. Most studies are conducted during continuous resting-state
conditions such as fixation on a cross-hair or eyes-closed rest.
Subjects are usually instructed simply to lie still in the scanner and
refrain from falling asleep. After data acquisition, two important data
analysis issues must be considered: how to account for non-neuronal
noise and how to identify spatial patterns of spontaneous activit
-- Accounting for non-neuronal noise.
--Identifying spatial patterns :- The simplest technique is to extract
the BOLD time course from a region of interest (called a seed region) and
determine the temporal correlation between this extracted signal and the time
course from all other brain voxels.

 Conclusions : -
 1.Spontaneous fluctuations. They are not random noise, but
are specifically correlated between functionally related brain
regions and relate to known anatomical systems. They cannot
be attributed to cardiac or respiratory factors, and they correlate
well with fluctuations in the power of highfrequency neuronal
activity.
 Spontaneous BOLD correlation patterns persist across different
resting states, including sleep and anaesthesia, suggesting that
they are an intrinsic property of the brain as opposed to being
the result of unconstrained mental activity.
 spontaneous BOLD fluctuations do not disappear during task
conditions, but continue, contributing to inter-trial variability in
measured BOLD responses and behaviour, we will refer to such
networks as temporally coherent networks (TCNs).

 2. Findings of DMN.
 The default mode network (DMN) is a network of brain regions that
are active when an individual is awake and at rest. The default mode
network is an interconnected and anatomically defined brain system
that preferentially activates when individuals focus on internal tasks
such as daydreaming, envisioning the future, retrieving memories,
and gauging others' perspectives.
 Other Rest State Networks : - which are more frequently reported include: -
 The DMN(posterior cingulate, inferior parietal lobes, and medial frontal gyrus) The
sensory/motor component,
 The executive control component,
 Three different visual components
 Two lateralized frontal/parietal components
 The auditory component and the temporal /parietal component.
These resting-state networks consist of anatomically separated, but functionally
connected regions displaying a high level of correlated BOLD signal activity.

References :
 1. Hubel, D. H. & Wiesel, T. N. Receptive fields, binocular interaction and functional
architecture in the cat’s visual cortex. J. Physiol. (London) 160, 106–154 (1962).
 2. Posner, M. I. & Raichle, M. E. Images of Mind (W. H. Freeman & Company, New York,
1994).
 3. Buzsaki, G. & Draguhn, A. Neuronal oscillations in cortical networks. Science 304,
1926–1929 (2004). An excellent introduction to the role of oscillations over a wide
frequency range in supporting cortical network structure.
 4. Varella, F., Lachaux, J.-P., Rodriguez, E. & Martinerie, J. The brainweb: phase
synchronization and large-scale integration. Nature Rev. Neurosci. 2, 229–239 (2001).
 5. Shulman, R. G., Rothman, D. L., Behar, K. L. & Hyder, F. Energetic basis of brain
activity: implications for neuroimaging. Trends Neurosci. 27, 489–495 (2004).
 6. Attwell, D. & Laughlin, S. B. An energy budget for signalling in the grey matter of the
brain. J. Cereb. Blood Flow Metab. 21, 1133–1145 (2001).
 7. Ames, A. I. CNS energy metabolism as related to function. Brain Res. Rev. 34, 42–68
(2000).
 8. Lennie, P. The cost of cortical computation. Curr. Biol. 13, 493–497 (2003).

 RESEARCH PAPER 5th
 TITLE : “Functional magnetic resonance imaging during emotion recognition in
social anxiety disorder: an activation likelihood meta-analysis”.
 KEY WORDS : ALE, social anxiety, generalized social phobia, SAD, meta-analysis,
fMRI
 ABSTRACT : Social anxiety disorder (SAD) is characterized by
abnormal fear and anxiety in social situations. Functional
magnetic resonance imaging (fMRI) is a brain imaging
technique that can be used to demonstrate neural activation to
emotionally salient stimuli,using the activation likelihood-
estimate (ALE) technique, in response to emotion recognition
tasks in individuals with SAD.

 METHODOLOGY : A systematic search of fMRI studies of neural
responses to socially emotive cues in SAD was undertaken. ALE
meta-analysis, a voxel based meta-analytic technique, was used
to estimate the most significant activations during emotional
recognition.
 CONCLUSION :
 Seven studies were eligible for inclusion in the meta-analysis, constituting a
total of 91 subjects with SAD, and 93 healthy controls.
 The most significant areas of activation during emotional vs.neutral stimuli in
individuals with SAD compared to controls were: bilateral amygdala, left
medial temporal lobe encompassing the entorhinal cortex, left medial aspect
of the inferior temporal lobe encompassing perirhinal cortex and
parahippocampus, right anterior cingulate, right globus pallidus, and distal tip
of right postcentral gyrus.
 The results are consistent with neuroanatomic models of the role of the
amygdala in fear conditioning, and the importance of the limbic circuitry in
mediating anxiety symptoms.

 References :
 1. American Psychiatric Association. (2000). Diagnostic and Statistical Manual of Mental Disorders, 4th
Edn Text Revision (DSM-IV-TR). Arlington, VA: American Psychiatric Association.
 2. Alvarez R. P., Biggs A., Chen G., Pine D. S., Grillon C. (2008). Contextual fear conditioning in
humans: cortical-hippocampal and amygdala contributions. J. Neurosci. 28, 6211–
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emotional expressions in generalized social phobia and generalized anxiety disorder: evidence for
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modulation of medial prefrontal cortex to self-referential comments in generalized social phobia.
Psychiatry Res. Neuroimaging 193, 38–45.10.1016/j.pscychresns.2010.12.016 [PMC free article]
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 5. Botvinick M., Watanabe T. (2007). From numerosity to ordinal rank: a gain-field model of serial order
representation in cortical working memory. J. Neurosci. 27, 8636– 8642.10.1523/JNEUROSCI.2110-
07.2007 [PubMed] [Cross Ref]
 6. Brodmann K. (1909). Vergleichende Lokalisationslehre der Grosshirnrinde. Leipzig: Verlag von
Johann Ambrosias Barth.
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subliminal arousing stimuli induces robust activation in the amygdala, hippocampus, anterior cingulate,
insular cortex and primary visual cortex: a systematic meta-analysis of fMRI studies. Neuroimage 59,
2962–2973.10.1016/j.neuroimage.2011.09.077 [PubMed] [Cross Ref]
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