Introduction to the Special Focus: The Affective
Neuroscience of Poverty
Robin Nusslock1 and Martha J. Farah2
Abstrakt
■ Growing up in poverty is associated with a heightened risk
for mental and physical health problems across the life span,
and there is a growing recognition of the role that social deter-
minants of health play in driving these outcomes and inequities.
How do the social conditions of poverty get under the skin to
influence biology, and through what mechanisms do the
stressors of poverty generate risk for a broad range of health
problems? The growing field examining the neuroscience of
socioeconomic status (SES) proposes that the brain is an entry
point or pathway through which poverty and adversity become
embedded in biology to generate these disparities. To date,
Jedoch, the majority of research on the neuroscience of SES
has focused on cognitive or executive control processes. Wie-
immer, the relationship between SES and brain systems involved
in affective or emotional processes may be especially important
for understanding social determinants of health. Entsprechend,
this Special Focus on The Affective Neuroscience of Poverty
invited contributions from authors examining the relationship
between SES and brain systems involved in generating and reg-
ulating emotions. In this editorial introduction, Wir (A) provide
an overview of the neuroscience of SES; (B) introduce each of
the articles in this Special Focus; Und (C) discuss the scientific,
treatment, and policy implications of studying the affective neu-
roscience of poverty. ■
Poverty is a powerful risk factor for mental and physical
health problems across the life span. Socioeconomic sta-
tus (SES) is associated with depression, anxiety, psychosis,
and academic achievement, as well as heart disease,
stroke, cancer, diabetes, and early mortality (McLaughlin,
Costello, Leblanc, Sampson, & Kessler, 2012; Adler &
Stewart, 2010; Kessler et al., 2005; Sirin, 2005). Da ist ein
growing recognition of the important role that social
determinants play in driving these mental and physical
health inequities (Braveman & Gottlieb, 2014). Sozial
determinants of health are the conditions in the environ-
ment where people are born, live, learn, arbeiten, and play
that affect a wide range of health and quality-of-life out-
comes (Marmot et al., 2008). An important question is,
how do the social conditions of poverty get under the skin
to influence the biology of a developing child? And
through what mechanisms do these social determinants
generate risk for such a broad set of mental and physical
health outcomes? Over the past decade, researchers have
begun to examine the role of the brain in answering these
Fragen (Noble & Giebler, 2020; Farah, 2017). From this
Perspektive, the brain is an entry point or pathway through
which poverty and adversity become embedded in biology
to generate health disparities (McEwen & Gianaros, 2010).
Gemeinsam, this small but growing field examining rela-
tionships between the brain, Armut, and health is
referred to as the neuroscience of SES.
1Nordwestliche Universität, Evanston, IL, 2Universität
Pennsylvania
© 2022 Massachusetts Institute of Technology
SES is construed as a dimension that varies from “worse
off” to “better off,” with those who are better off having
more material resources (z.B., Einkommen) and nonmaterial
resources, including education and neighborhood quality.
Historically, SES has been relegated to the status of a covar-
iate or confound in the field of neuroscience. Jedoch,
there is increasing evidence that the stress of living in pov-
erty affects the developing brain in a manner that deserves
its own investigation (Noble, Engelhardt, et al., 2015; Brito
& Noble, 2014). The growth of knowledge on this topic is
apparent from the fact that there were only a handful of
studies on the neural correlates of SES in early reviews
(Raizada & Kishiyama, 2010; Hackman & Farah, 2009),
compared with dozens of relevant studies today. We now
know from neurophysiology and both structural and func-
tional imaging studies that early exposure to poverty is
associated with alterations in brain systems involved in a
variety of cognitive processes, including executive control,
Erinnerung, and language (see Johnson, Riis, & Noble, 2016,
für eine Rezension). Some of these studies report that neural
alterations mediate the linkage between poverty exposure
and cognitive processes (Hair, Hanson, Wolfe, & Pollak,
2015; Noble, Houston, et al., 2015; Mackey et al., 2015),
suggesting they are not simply correlates of SES, but pos-
sible mechanistic pathways to outcomes that matter.
Most research on the neuroscience of SES has focused
on cognitive processes. This work builds on the cognitive
neuroscience of language, Erinnerung, and executive func-
tion and holds promise for understanding the SES achieve-
ment gap, as well as later occupational success (Farah,
Zeitschrift für kognitive Neurowissenschaften 34:10, S. 1806–1809
https://doi.org/10.1162/jocn_a_01899
l
D
Ö
w
N
Ö
A
D
e
D
F
R
Ö
M
H
T
T
P
:
/
/
D
ich
R
e
C
T
.
M
ich
T
.
e
D
u
/
J
/
Ö
C
N
A
R
T
ich
C
e
–
P
D
l
F
/
/
/
3
4
1
0
1
8
0
6
2
0
4
1
8
1
5
/
/
J
Ö
C
N
_
A
_
0
1
8
9
9
P
D
.
F
B
j
G
u
e
S
T
T
Ö
N
0
7
S
e
P
e
M
B
e
R
2
0
2
3
2017). Jedoch, it may be especially important to examine
the relationship between SES and brain systems involved
in affective processes if we’re to better understand social
determinants of mental and physical health. Chronic
adversity, including poverty, negatively affects the struc-
ture and function of brain regions involved in emotion,
including the amygdala, insula, ventral striatum, and por-
tions of the pFC (see McLaughlin, Weissman, & Bitran,
2019, für eine Rezension). These same brain regions are implica-
ted in numerous mental health problems, including anxiety,
depression, and various externalizing disorders (Keren et al.,
2018; Baskin-Sommers, 2016; Shackman et al., 2016), all of
which correlate with SES (McLaughlin et al., 2012; Lorant
et al., 2003). They also regulate homeostatic processes impli-
cated in chronic inflammation and stress-related physical
diseases, including metabolic syndrome, coronary heart
Krankheit, and autoimmune conditions (see Nusslock &
Müller, 2016 für eine Rezension). Daher, multiple lines of evidence
suggest that emotional brain systems may be affected by the
stressors of poverty and contribute to the mechanistic
pathways through which SES affects health. Entsprechend,
this Special Focus on The Affective Neuroscience of Poverty
is intended to showcase research on SES and brain systems
involved in generating and regulating emotions. In keeping
with the Journal of Cognitive Neuroscience’s emphasis on
basic science over diagnostic and/or treatment-relevant
arbeiten, the articles in this Special Focus present findings
from basic affective neuroscience rather than investigations
of patient populations.
The first set of articles in this Special Focus examined
the relationship between SES and neural responses
to emotional stimuli. Alvarez, Rudolf, Cohen, Und
Muscatell (2022) report that individuals with a lower
socioeconomic position displayed greater activity to both
positive and negative images in brain regions involved in
emotion processing and homeostasis. Nächste, White,
Nusslock, and Miller (2022) report that low SES was asso-
ciated with greater activation in brain regions involved in
attention to both reward and loss cues and reduced differ-
entiation in the brain between reward and loss feedback.
Both of these results are consistent with the concept of the
“scarcity mindset,” which suggests that individuals living
with minimal resources are sensitive to cues of both gain
and loss and that the metabolic demand of this hyper-
sensitivity can generate health problems overtime (Shah,
Shafir, & Mullainathan, 2015).
The next set of studies examined mediators and moder-
ators of the relationships between SES, brain structure and
Funktion, and emotional states and traits. Hao, Bertolero,
and Farah (2022) tested whether healthy young adults of
low SES generally experience more negative emotions
and whether the volume of the amygdala and its reactivity
to emotional stimuli mediate the association between
SES and negative emotions. Weissman et al. (2022) inves-
tigated the neural mechanisms through which two
dimensions of adversity—threat and deprivation—might
contribute to SES disparities in psychopathology. Sie
report that greater exposure to threat, but not deprivation,
was associated with higher activation in the dorsomedial
pFC and precuneus to fearful faces and that precuneus
activation mediated the association between SES and post-
traumatic symptoms. Hackman et al. (2022) tested
whether SES moderated the relationship between school
climate, which is important for children’s socioemotional
Entwicklung, and cortical thickness, cortical surface area,
and subcortical volume. These three studies help us
understand the neural mechanisms through which pov-
erty may facilitate negative emotions and under what con-
ditions these mechanistic associations may emerge.
The last set of articles is consistent with the growing rec-
ognition in human neuroscience of the importance of
moving beyond only examining brain regions in isolation
of each other and to also assess functional and structural
connections between brain regions. This is premised on
the fact that both normative and nonnormative mental
states likely emerge from distributed neural networks,
rather than any one particular area of the brain in isolation
(Bassett, Xia, & Satterthwaite, 2018; Braun et al., 2018).
Ip et al. (2022) present findings from the Adolescent
Brain Cognitive Development study on the associations
between socioeconomic disadvantage, resting-state func-
tional connectivity between the medial OFC and amyg-
dala, and internalizing symptoms in 9- to 10-year-old
youth. Hardi et al. (2022) used diffusion imaging to
examine the relationship between white matter structural
connectivity within frontolimbic structures and material
hardship at different ages along the developmental spec-
trum. They report that the associations between fronto-
limbic connectivity and material hardship differ across
prefrontal regions and developmental periods, providing
support for potential windows of plasticity for structural
circuits that support emotion.
There are at least three ways that the research exempli-
fied here can benefit science and society. Erste, by elucidat-
ing the mechanisms through which poverty becomes
embedded in biology, we will better understand an impor-
tant source of individual differences in thinking, feeling,
and health. This research will inevitably bring attention
to environmental factors and structural inequities in our
society and to our collective responsibility to improve
the environment for low SES individuals. Despite the
biological nature of brain differences, it does not follow
that they are genetically caused; a substantial proportion
of SES effects on neuroanatomy can be attributed to envi-
ronmental causes (Kweon et al., 2022). A biological
approach to SES disparities in brain and health in no way
blames the poor or implies that DNA is destiny. Zweite,
like any basic or preclinical science addressing an impor-
tant social or medical problem, we anticipate that this
work will eventually inform prevention and intervention
strategies. Although the neuroscience of SES is a young
field, it has already been used to better understand the
effects of interventions on low-income children (Farah
et al., 2021; Brody et al., 2017). Dritte, this work may help
Nusslock and Farah
1807
l
D
Ö
w
N
Ö
A
D
e
D
F
R
Ö
M
H
T
T
P
:
/
/
D
ich
R
e
C
T
.
M
ich
T
.
e
D
u
/
J
/
Ö
C
N
A
R
T
ich
C
e
–
P
D
l
F
/
/
/
3
4
1
0
1
8
0
6
2
0
4
1
8
1
5
/
/
J
Ö
C
N
_
A
_
0
1
8
9
9
P
D
.
F
B
j
G
u
e
S
T
T
Ö
N
0
7
S
e
P
e
M
B
e
R
2
0
2
3
facilitate policies that target structural inequities in our
society that contribute to or drive health disparities. Als
noted by Muna Abdi, an Education and Racial Equity Con-
sultant, “instead of praising people for being resilient,
change the systems that are making them vulnerable”
(personal communication with R. N.). There is early evi-
dence that such changes can have a salubrious effect on
the brain and body. In one of the first studies of its kind,
Troller-Renfree et al. (2022) demonstrated that a modest
monthly cash transfer to low-income families had a causal
impact on infant brain activity that has been associated
with the development of subsequent cognitive skills. Wir
believe that the articles in this Special Focus and the neu-
roscience of SES more broadly provide a new source of
support for investment in the needs of individuals and
families in poverty.
Many fields, including psychology, Soziologie, epidemiol-
Ogy, and economics, have tried to understand the causes
and consequences of health disparities. We are not
suggesting that neural explanations replace these important
perspectives, but that they can provide a complimentary
viewpoint that can help us understand the mechanisms
through which the socioeconomic environment leads to
socioeconomic disparities. Letzten Endes, the value of neuro-
science for understanding SES and facilitating interventions
and policies is an empirical question that needs to be inves-
tigated. To facilitate this, we recommend that studies of
human neuroscience consider including measures of SES.
We also recommend that we as a field move beyond simply
considering SES as a nuisance variable or covariate and
instead examine its associations with primary variables
and test for moderation and/or mediation. Endlich, we argue
that it is time for us as a field to move beyond relying on
predominately middle- to upper-class participants or under-
graduate subject pools and to include more participants
from lower SES backgrounds. This will help us generate
questions and findings that are more generalizable and
better position us to apply our work to important societal
issues such as poverty and health disparities.
Reprint requests should be sent to Robin Nusslock, Department
of Psychology, Nordwestliche Universität, 2029 Sheridan Road,
Evanston, IL 60208, oder per E-Mail: nusslock@northwestern.edu.
Informationen zur Finanzierung
National Institute of Mental Health (https://dx.doi.org/10
.13039/100000025), Fördernummern: R01 MH123473, R01
MH129911. National Institute on Drug Abuse (https://dx.doi
.org/10.13039/100000026), grant number: P50 DA051361.
Vielfalt in der Zitierpraxis
Retrospektive Analyse der Zitate in jeder Artikelveröffentlichung-
in dieser Zeitschrift aufgeführt von 2010 Zu 2021 offenbart eine hartnäckige
Muster des Ungleichgewichts zwischen den Geschlechtern: Although the proportions
of authorship teams (categorized by estimated gender
identification of first author/ last author) publishing in
the Journal of Cognitive Neuroscience ( JoCN ) during this
period were M(ein)/M = .407, W(Oman)/M = .32, M/W =
.115, und W/ W = .159, the comparable proportions for the
articles that these authorship teams cited were M/M =
.549, W/M = .257, M/W = .109, und W/ W = .085 (Postle
and Fulvio, JoCN, 34:1, S. 1-3). Folglich, JoCN
encourages all authors to consider gender balance
explicitly when selecting which articles to cite and gives
them the opportunity to report their article’s gender cita-
tion balance.
VERWEISE
Adler, N. E., & Stewart, J. (2010). Health disparities across the
lifespan: Meaning, Methoden, and mechanisms. Annals of the
New York Academy of Sciences, 1186, 5–23. https://doi.org
/10.1111/j.1749-6632.2009.05337.x, PubMed: 20201865
Alvarez, G. M., Rudolf, M. D., Cohen, J. R., & Muscatell,
K. A. (2022). Lower socioeconomic position is associated
with greater activity in and integration within an
allostatic-interoceptive brain network in response to affective
Reize. Zeitschrift für kognitive Neurowissenschaften, 34, 1906–1927.
https://doi.org/10.1162/jocn_a_01830, PubMed: 35139207
Baskin-Sommers, A. R. (2016). Dissecting antisocial behavior:
The impact of neural, genetic, and environmental factors.
Clinical Psychological Science, 4, 500–510. https://doi.org/10
.1177/2167702615626904
Bassett, D. S., Xia, C. H., & Satterthwaite, T. D. (2018).
Understanding the emergence of neuropsychiatric disorders
with network neuroscience. Biologische Psychiatrie: Kognitiv
Neuroscience and Neuroimaging, 3, 742–753. https://doi
.org/10.1016/j.bpsc.2018.03.015, PubMed: 29729890
Braun, U., Schäfer, A., Betzel, R. F., Tost, H., Meyer-Lindenberg,
A., & Bassett, D. S. (2018). From maps to multi-dimensional
network mechanisms of mental disorders. Neuron, 97, 14–31.
https://doi.org/10.1016/j.neuron.2017.11.007, PubMed:
29301099
Braveman, P., & Gottlieb, L. (2014). The social determinants of
Gesundheit: It’s time to consider the causes of the causes. Public
Health Reports, 129, 19–31. https://doi.org/10.1177
/00333549141291S206, PubMed: 24385661
Brito, N. H., & Noble, K. G. (2014). Socioeconomic status and
structural brain development. Frontiers in Neuroscience,
8, 276. https://doi.org/10.3389/fnins.2014.00276, PubMed:
25249931
Brody, G. H., Gray, J. C., Yu, T., Barton, A. W., Beach, S. R. H.,
Galvan, A., et al. (2017). Protective prevention effects on
the association of poverty with brain development. JAMA
Pädiatrie, 171, 46–52. https://doi.org/10.1001/jamapediatrics
.2016.2988, PubMed: 27893880
Farah, M. J. (2017). The neuroscience of socioeconomic status:
Correlates, causes, and consequences. Neuron, 96, 56–71.
https://doi.org/10.1016/j.neuron.2017.08.034, PubMed:
28957676
Farah, M. J., Sternberg, S., Nichols, T. A., Duda, J. T., Lohrenz,
T., Luo, Y., et al. (2021). Randomized manipulation of early
cognitive experience impacts adult brain structure. Zeitschrift
of Cognitive Neuroscience, 33, 1197–1209. https://doi.org/10
.1162/jocn_a_01709, PubMed: 34428792
Hackman, D. A., Duan, L., McConnell, E. E., Jung Lee, W., Beak,
A. S., & Kraemer, D. J. M. (2022). School climate, cortical
Struktur, and socioemotional functioning: Associations
1808
Zeitschrift für kognitive Neurowissenschaften
Volumen 34, Nummer 10
l
D
Ö
w
N
Ö
A
D
e
D
F
R
Ö
M
H
T
T
P
:
/
/
D
ich
R
e
C
T
.
M
ich
T
.
e
D
u
/
J
/
Ö
C
N
A
R
T
ich
C
e
–
P
D
l
F
/
/
/
3
4
1
0
1
8
0
6
2
0
4
1
8
1
5
/
/
J
Ö
C
N
_
A
_
0
1
8
9
9
P
D
.
F
B
j
G
u
e
S
T
T
Ö
N
0
7
S
e
P
e
M
B
e
R
2
0
2
3
across family income levels. Zeitschrift für Kognition
Neurowissenschaften, 34, 1842–1865. https://doi.org/10.1162/jocn_a
_01833, PubMed: 35171285
Hackman, D. A., & Farah, M. J. (2009). Socioeconomic status and
the developing brain. Trends in den Kognitionswissenschaften, 13, 65–73.
https://doi.org/10.1016/j.tics.2008.11.003, PubMed: 19135405
Hair, N. L., Hanson, J. L., Wolfe, B. L., & Pollak, S. D. (2015).
Association of child poverty, brain development, and academic
achievement. JAMA Pediatrics, 169, 822–829. https://doi.org
/10.1001/jamapediatrics.2015.1475, PubMed: 26192216
Hao, H., Bertolero, M., & Farah, M. J. (2022). Anger, fear, Und
sadness: Relations to socioeconomic status and the amygdala.
Zeitschrift für kognitive Neurowissenschaften, 34, 1928–1938. https://doi
.org/10.1162/jocn_a_01892, PubMed: 35900864
Hardi, F. A., Goetschius, L. G., Peckins, M. K., Brooks-Gunn, J.,
McLanahan, S. S., McLoyd, V., et al. (2022). Differential
developmental associations of material hardship exposure
and adolescent amygdala-prefrontal cortex white matter
Konnektivität. Zeitschrift für kognitive Neurowissenschaften, 34,
1866–1891. https://doi.org/10.1162/jocn_a_01801, PubMed:
34942644
Ip, K. ICH., Sisk, L. M., Horien, C., Conley, M. ICH., Rapuano, K. M.,
Rosenberg, M. D., et al. (2022). Associations among
household and neighborhood socioeconomic disadvantages,
resting-state frontoamygdala connectivity, and internalizing
symptoms in youth. Zeitschrift für kognitive Neurowissenschaften, 34,
1810–1841. https://doi.org/10.1162/jocn_a_01826, PubMed:
35104356
Johnson, S. B., Riis, J. L., & Noble, K. G. (2016). State of the art
Rezension: Poverty and the developing brain. Pädiatrie, 137,
e20153075. https://doi.org/10.1542/peds.2015-3075, PubMed:
26952506
Keren, H., O’Callaghan, G., Vidal-Ribas, P., Buzzell, G. A.,
Brotman, M. A., Leibenluft, E., et al. (2018). Reward
processing in depression: A conceptual and meta-analytic
review across fMRI and EEG studies. American Journal of
Psychiatrie, 11, 1111–1120. https://doi.org/10.1176/appi.ajp
.2018.17101124, PubMed: 29921146
Kessler, R. C., Berglund, P., Demler, O., Jin, R., Merikangas,
K. R., & Walters, E. E. (2005). Lifetime prevalence and
age-of-onset distributions of DSM-IV disorders in the
National Comorbidity Survey Replication. Archives of
General Psychiatry, 62, 593–602. https://doi.org/10.1001
/archpsyc.62.6.593, PubMed: 15939837
Kweon, H., Aydoğan, G., Dagher, A., Bzdok, D., Ruff, C. C.,
Nave, G., et al. (2022). Human brain anatomy reflects
separable genetic and environmental components of
socioeconomic status. Science Advances, 8, eabm2923.
https://doi.org/10.1126/sciadv.abm2923, PubMed: 35584223
Lorant, V., Deliege, D., Eaton, W., Robert, A., Philippot, P.,
& Ansseau, M. (2003). Socioeconomic inequalities in
depression: A meta-analysis. American Journal of
Epidemiology, 157, 98–112. https://doi.org/10.1093/aje
/kwf182, PubMed: 12522017
Mackey, A. P., Finn, A. S., Leonard, J. A., Jacoby-Senghor, D. S.,
Westen, M. R., Gabriela, C. F. O., et al. (2015). Neuroanatomical
correlates of the income-achievement gap. Psychological
Wissenschaft, 26, 925–933. https://doi.org/10.1177
/0956797615572233, PubMed: 25896418
Marmot, M., Friel, S., Glocke, R., Houweling, T. A. J., Taylor, S., &
The Commission on Social Determinants of Health. (2008).
Closing the gap in a generation: Health equity through action
on the social determinants of health. Lancet, 372, 1661–1669.
https://doi.org/10.1016/S0140-6736(08)61690-6, PubMed:
18994664
McEwen, B. S., & Gianaros, P. J. (2010). Central role of the brain
in stress and adaptation: Links to socioeconomic status,
Gesundheit, und Krankheit. Annalen der New York Academy of
Wissenschaften, 1186, 190–222. https://doi.org/10.1111/j.1749-6632
.2009.05331.X, PubMed: 20201874
McLaughlin, K. A., Costello, E. J., Leblanc, W., Sampson, N. A., &
Kessler, R. C. (2012). Socioeconomic status and adolescent
mental disorders. American Journal of Public Health,
102, 1742–1750. https://doi.org/10.2105/AJPH.2011.300477,
PubMed: 22873479
McLaughlin, K. A., Weissman, D., & Bitran, D. (2019).
Childhood adversity and neural development: A systematic
Rezension. Annual Review of Developmental Psychology, 1,
277–312. https://doi.org/10.1146/annurev-devpsych-121318
-084950, PubMed: 32455344
Noble, K. G., Engelhardt, L. E., Brito, N. H., Mack, L. J., Nail, E. J.,
Angal, J., et al. (2015). Socioeconomic disparities in
neurocognitive development in the first two years of life.
Developmental Psychobiology, 57, 535–551. https://doi.org
/10.1002/dev.21303, PubMed: 25828052
Noble, K. G., & Giebler, M. A. (2020). The neuroscience of
socioeconomic inequality. Current Opinion in Behavioral
Wissenschaften, 36, 23–28. https://doi.org/10.1016/j.cobeha.2020.05
.007, PubMed: 32719820
Noble, K. G., Houston, S. M., Brito, N. H., Bartsch, H., Kann, E.,
Kuperman, J. M., et al. (2015). Family income, parental
education and brain structure in children and adolescents.
Naturneurowissenschaften, 18, 773–778. https://doi.org/10.1038
/nn.3983, PubMed: 25821911
Nusslock, R., & Müller, G. E. (2016). Early-life adversity and
physical and emotional health across the lifespan: A
neuro-immune network hypothesis. Biologische Psychiatrie,
80, 23–32. https://doi.org/10.1016/j.biopsych.2015.05.017,
PubMed: 26166230
Raizada, R. D. S., & Kishiyama, M. M. (2010). Effects of
socioeconomic status on brain development, and how
cognitive neuroscience may contribute to levelling the
playing field. Grenzen der menschlichen Neurowissenschaften, 4, 3. https://
doi.org/10.3389/neuro.09.003.2010, PubMed: 20161995
Shackman, A. J., Tromp, D. P. M., Stockbridge, M. D., Kaplan,
C. M., Tillman, R. M., & Fuchs, A. S. (2016). Dispositional
negativity: An integrative psychological and neurobiological
Perspektive. Psychological Bulletin, 142, 1275–1314. https://
doi.org/10.1037/bul0000073, PubMed: 27732016
Shah, A. K., Shafir, E., & Mullainathan, S. (2015). Scarcity frames
value. Psychological Science, 26, 402–412. https://doi.org/10
.1177/0956797614563958, PubMed: 25676256
Sirin, S. R. (2005). Socioeconomic status and academic
achievement: A meta-analytic review of research. Review of
Educational Research, 75, 417–453. https://doi.org/10.3102
/00346543075003417
Troller-Renfree, S. V., Costanzo, M. A., Duncan, G. J., Magnuson,
K., Gennetian, L. A., Yoshikawa, H., et al. (2022). The impact
of a poverty reduction intervention on infant brain activity.
Verfahren der Nationalen Akademie der Wissenschaften, USA.,
119, e2115649119. https://doi.org/10.1073/pnas.2115649119,
PubMed: 35074878
Weissman, D. G., Rosen, M. L., Colich, N., Sambrook, K. A.,
Lengua, L. J., Sheridan, M., et al. (2022). Exposure to violence
as an environmental pathway linking low socioeconomic
status with altered neural processing of threat and
adolescent psychopathology. Zeitschrift für Kognition
Neurowissenschaften, 34, 1892–1905. https://doi.org/10.1162/jocn_a
_01825, PubMed: 35104853
White, S. F., Nusslock, R., & Müller, G. E. (2022). Low
socioeconomic status is associated with a greater neural
response to both rewards and losses. Zeitschrift für Kognition
Neurowissenschaften, 34, 1939–1951. https://doi.org/10.1162/jocn_a
_01821, PubMed: 35061015
Nusslock and Farah
1809
l
D
Ö
w
N
Ö
A
D
e
D
F
R
Ö
M
H
T
T
P
:
/
/
D
ich
R
e
C
T
.
M
ich
T
.
e
D
u
/
J
/
Ö
C
N
A
R
T
ich
C
e
–
P
D
l
F
/
/
/
3
4
1
0
1
8
0
6
2
0
4
1
8
1
5
/
/
J
Ö
C
N
_
A
_
0
1
8
9
9
P
D
.
F
B
j
G
u
e
S
T
T
Ö
N
0
7
S
e
P
e
M
B
e
R
2
0
2
3