Understanding brain networks and brain organization
Open accessAbstract
What is the relationship between brain and behavior? The answer to this question necessitates characterizing the mapping between structure and function. The aim of this paper is to discuss broad issues surrounding the link between structure and function in the brain that will motivate a network perspective to understanding this question. However, as others in the past, I argue that a network perspective should supplant the common strategy of understanding the brain in terms of individual regions. Whereas this perspective is needed for a fuller characterization of the mind-brain, it should not be viewed as panacea. For one, the challenges posed by the many-to-many mapping between regions and functions is not dissolved by the network perspective. Although the problem is ameliorated, one should not anticipate a one-to-one mapping when the network approach is adopted. Furthermore, decomposition of the brain network in terms of meaningful clusters of regions, such as the ones generated by community-finding algorithms, does not by itself reveal "true" subnetworks. Given the hierarchical and multi-relational relationship between regions, multiple decompositions will offer different "slices" of a broader landscape of networks within the brain. Finally, I described how the function of brain regions can be characterized in a multidimensional manner via the idea of diversity profiles. The concept can also be used to describe the way different brain regions participate in networks.
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Multiple structural network configurations can theoretically give rise to the same apparent aberrations in function.
“multiple structural network configurations can theoretically give rise to the same apparent aberrations in function – this is essentially the ‘many-to-many mappings’ problem very nicely described in (Pessoa, 2014).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Pessoa, 2014
There are numerous lines of evidence to suggest that brain-behavior relationships are not simply one-to-one.
“There are numerous lines of evidence to suggest that brain-behavior relationships are not simply one-to-one (Pessoa, 2014).”
From Investigating functional brain network integrity using a traditional and novel categorical scheme for neurodevelopmental disorders (2019) · cites this paper as Pessoa, 2014
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BackgroundMeasuring functional connectivity during distinct stages of a cognitive task
Rissman, J., Gazzaley, A. H., & D’Esposito, M. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.06.035 · Cited by 894 · cited 1× · see citing works
“For example, the functional connectivity between two regions with known (or presumed) structural connections can increase or decrease as a function of several variables, including task performance [103], motivation [104], and emotion [105].”
BackgroundChang, L. J., Yarkoni, T., Khaw, M. W., & Sanfey, A. G. (2013) · Cerebral Cortex · doi:10.1093/cercor/bhs065 · Cited by 879 · see citing works
A Weighted and Directed Interareal Connectivity Matrix for Macaque Cerebral Cortex
Markov, N. T., Ercsey-Ravasz, M. M., Ribeiro Gomes, A. R., Lamy, C., Magrou, L., Vezoli, J., Misery, P., Falchier, A., Quilodran, R., Gariel, M. A., et al. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhs270 · Cited by 857 · cited 1× · see citing works
“global level, Markov, Kennedy and colleagues injected a retrograde tracer into 29 cortical areas distributed relatively evenly across the macaque cortex [40], allowing them to determine connectivity for a complete 29 × 29 connectivity graph.”
BackgroundCerebral hemisphere regulation of motivated behavior
Swanson, L. W. (2000) · Brain Research · doi:10.1016/s0006-8993(00)02905-x · Cited by 846 · cited 1× · see citing works
“The hypothalamus is probably the largest source of nonthalamic direct input to cortex, as reviewed in detail by Larry Swanson and colleagues [29, 83].”
Ghashghaei, H. T., Hilgetag, C. C., & Barbas, H. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.09.046 · Cited by 845 · cited 1× · see citing works
“In addition to substantial connections between the amygdala and both medial and orbital aspects of prefrontal cortex, recent findings indicate that bidirectional connectivity is present also along the lateral surface [81] – although the connections are relatively weak.”
BackgroundInferring mental states from neuroimaging data: from reverse inference to large-scale decoding
Poldrack, R. A. (2011) · Neuron · doi:10.1016/j.neuron.2011.11.001 · Cited by 821 · cited 6× · see citing works
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BackgroundResultInfluentialNonparametric estimation of Shannon’s index of diversity when there are unseen species in sample
Chao, A., & Shen, T. (2003) · Environmental and Ecological Statistics · doi:10.1023/a:1026096204727 · Cited by 806 · cited 1× · see citing works
“where S = 20 was the number of task domains and pi corresponded to the ith domain proportion (for an improved Shannon index, see [158]).”
BackgroundMosaic evolution of brain structure in mammals
Barton, R. A., & Harvey, P. H. (2000) · Nature · doi:10.1038/35016580 · Cited by 797 · see citing works
The Brain Binds Entities and Events by Multiregional Activation from Convergence Zones
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BackgroundInfluentialAnatomy of hierarchy: Feedforward and feedback pathways in macaque visual cortex
Markov, N. T., Vezoli, J., Chameau, P., Falchier, A., Quilodran, R., Huissoud, C., Lamy, C., Misery, P., Giroud, P., Ullman, S., et al. (2014) · Journal of Comparative Neurology · doi:10.1002/cne.23458 · Cited by 759 · cited 1× · see citing works
“11 Some researchers have suggested that hierarchical information can be resolved once laminar information is established for the regions involved (thus presumably helping determine “feedforward” and “feedback” connections”) [150].”
BackgroundAge-related changes in modular organization of human brain functional networks
Meunier, D., Achard, S., Morcom, A., & Bullmore, E. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.09.062 · Cited by 756 · see citing works
Communicability in complex networks
Estrada, E., & Hatano, N. (2008) · Physical Review E · doi:10.1103/physreve.77.036111 · Cited by 719 · cited 4× · see citing works
“Counter intuitively, as described by Estrada and Hatano [133], “information” can in fact spread along non-shortest paths (see also [134]; [135]).”
BackgroundInfluentialEvidence for hubs in human functional brain networks
Power, J. D., Schlaggar, B. L., Lessov-Schlaggar, C. N., & Petersen, S. E. (2013) · Neuron · doi:10.1016/j.neuron.2013.07.035 · Cited by 716 · cited 1× · see citing works
“In this context, Power and colleagues [132] discuss the shortcomings of using the measure of degree to define node importance and suggest other measures instead.”
BackgroundFurther contributions to the study of the evolution of the forebrain
Johnston, J. B. (1923) · The Journal of Comparative Neurology · doi:10.1002/cne.900350502 · Cited by 667 · see citing works
Combinatorial amygdalar inputs to hippocampal domains and hypothalamic behavior systems.
Petrovich, G., Canteras, N., & Swanson, L. (2001) · Brain research. Brain research reviews · doi:10.1016/s0165-0173(01)00080-7 · Cited by 628 · cited 3× · see citing works
“For instance, Swanson and colleagues reported that on the order of 600 connections of the amygdala were known at the time of their publication [30], and estimated that the total would likely be closer to 1000.”
BackgroundCortical high-density counterstream architectures
Markov, N. T., Ercsey-Ravasz, M., Van Essen, D. C., Knoblauch, K., Toroczkai, Z., & Kennedy, H. (2013) · Science · doi:10.1126/science.1238406 · Cited by 616 · cited 1× · see citing works
“In recent computational analyses, Markov and colleagues [42] suggest the intriguing possibility that, at higher densities, rewiring (i.”
BackgroundGraph-based network analysis of resting-state functional MRI
Wang, J. (2010) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2010.00016 · Cited by 614 · see citing works
Postuma, R. B., & Dagher, A. (2006) · Cerebral Cortex · doi:10.1093/cercor/bhj088 · Cited by 579 · cited 3× · see citing works
“Using a similar approach, Postuma and Dagher [120] identified patterns of co-activation between the cortex and striatum that appear to reflect the cortico-striatal loops proposed by Alexander and colleagues [67].”
MethodStructural foundations of resting-state and task-based functional connectivity in the human brain
Hermundstad, A. M., Bassett, D. S., Brown, K., Aminoff, E., Clewett, D., Freeman, S., Frithsen, A., Johnson, A., Tipper, C. M., Miller, M. B., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1219562110 · Cited by 559 · cited 3× · see citing works
“21 Hermundstad and colleagues [39], who averaged the values of several network diagnostics across one hundred partitions.”
BackgroundInfluentialThe thalamus is more than just a relay
Sherman, S. M. (2007) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2007.07.003 · Cited by 559 · cited 1× · see citing works
“One suggestion [74] is that the pulvinar participates in cortical communication, with direct cortical connections between two areas supplemented by an indirect pathway coursing through the pulvinar or other higher-order thalamic nuclei (Fig.”
BackgroundHumans and great apes share a large frontal cortex
Semendeferi, K., Lu, A., Schenker-Ahmed, N. M., & Damasio, H. (2002) · Nature Neuroscience · doi:10.1038/nn814 · Cited by 546 · cited 1× · see citing works
“By comparison, the volume of the human neocortex is 24% larger than expected for a primate of our brain size [92], whereas the human frontal lobe, frequently assumed to be enlarged, is approximately the size expected for an ape of human brain size [93].”
BackgroundAn investigation of functional and anatomical connectivity using magnetic resonance imaging
Koch, M. A., Norris, D. G., & Hund-Georgiadis, M. (2002) · NeuroImage · doi:10.1006/nimg.2001.1052 · Cited by 509 · cited 1× · see citing works
“Koch and colleagues compared anatomical and functional connectivity between cortical patches on adjacent cortical gyri [113].”
BackgroundTowards a network theory of cognition
McIntosh, A. R. (2000) · Neural Networks · doi:10.1016/s0893-6080(00)00059-9 · Cited by 500 · cited 1× · see citing works
“What determines a region’s affiliation? Here, the importance of the context within which a brain region is operating must be considered [47].”
BackgroundInferring psychological significance from physiological signals.
Cacioppo, J. T., & Tassinary, L. G. (1990) · American Psychologist · doi:10.1037//0003-066x.45.1.16 · Cited by 486 · see citing works
Inferring psychological significance from physiological signals.
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“Cacioppo JT, Tassinary LG. Inferring psychological significance from physiological signals.”
BackgroundInfluentialSudden Emergence of a Giantk-Core in a Random Graph
Pittel, B. G., Spencer, J., & Wormald, N. (1996) · Journal of Combinatorial Theory Series B · doi:10.1006/jctb.1996.0036 · Cited by 452 · cited 1× · see citing works
“8 One way to evaluate this is to use k-shell decomposition [131].”
MethodDegeneracy and cognitive anatomy
Price, C. J., & Friston, K. J. (2002) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(02)01976-9 · Cited by 444 · cited 1× · see citing works
“In particular, the existence of two or more degenerate systems that do not overlap precludes the existence of a single necessary area for a given function [7].”
BackgroundClasses of complex networks defined by role-to-role connectivity profiles
Guimerà, R., Sales‐Pardo, M., & Amaral, L. A. N. (2006) · Nature Physics · doi:10.1038/nphys489 · Cited by 428 · cited 1× · see citing works
“5) [63,64] (“importance” will be further refined in a later section).”
BackgroundCognitive effort drives workspace configuration of human brain functional networks
Kitzbichler, M. G., Henson, R. N. A., Smith, M. L., Nathan, P. J., & Bullmore, E. T. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.0440-11.2011 · Cited by 427 · cited 1× · see citing works
“An analysis of MEG data has suggested that greater cognitive effort is associated with the emergence of a less modular network topology [127].”
MethodSimultaneously Recorded Trains of Action Potentials: Analysis and Functional Interpretation
Gerstein, G. L., & Perkel, D. H. (1969) · Science · doi:10.1126/science.164.3881.828 · Cited by 417 · cited 1× · see citing works
“concept that was initially devised to characterize how neurons interact and was defined as the “temporal coherence” among the activity of different neurons, as measured by crosscorrelating their spike trains [94-96].”
BackgroundThe functional logic of cortico-pulvinar connections
Shipp, S. (2003) · Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences · doi:10.1098/rstb.2002.1213 · Cited by 411 · cited 3× · see citing works
“Indeed, sites in the dorsal pulvinar may be connected with relatively distal parts of the brain, such as parietal and frontal cortex [70].”
BackgroundThe primate neocortex in comparative perspective using magnetic resonance imaging
Rilling, J. K., & Insel, T. R. (1999) · Journal of Human Evolution · doi:10.1006/jhev.1999.0313 · Cited by 406 · cited 1× · see citing works
“By comparison, the volume of the human neocortex is 24% larger than expected for a primate of our brain size [92], whereas the human frontal lobe, frequently assumed to be enlarged, is approximately the size expected for an ape of human brain size [93].”
BackgroundLaird, A., Lancaster, J., & Fox, P. (2007) · Neuroinformatics · doi:10.1385/ni:3:1:065 · Cited by 379 · see citing works
Functional Coactivation Map of the Human Brain
Toro, R., Fox, P. T., & Paus, T. (2008) · Cerebral Cortex · doi:10.1093/cercor/bhn014 · Cited by 378 · cited 6× · see citing works
“[119] identified three functional networks: a fronto-parietal attention network, a resting-state network, and a motor network.”
BackgroundMethodInfluentialAnatomic basis of cognitive-emotional interactions in the primate prefrontal cortex
Barbas, H. (1995) · Neuroscience & Biobehavioral Reviews · doi:10.1016/0149-7634(94)00053-4 · Cited by 371 · cited 2× · see citing works
“The importance of networks also was emphasized by Barbas in the domain of emotion and cognition [27].”
BackgroundMethodThe corticothalamocortical circuit drives higher-order cortex in the mouse
Theyel, B. B., Llano, D. A., & Sherman, S. M. (2010) · Nature Neuroscience · doi:10.1038/nn.2449 · Cited by 366 · cited 2× · see citing works
“[75], “corticothalamocortical information transfer may represent an important addition to, or even replacement of, the current dogma that corticocortical transfer of primary information exclusively involves direct corticocortical pathways.”
BackgroundReward Reduces Conflict by Enhancing Attentional Control and Biasing Visual Cortical Processing
Padmala, S., & Pessoa, L. (2011) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00011 · Cited by 362 · cited 2× · see citing works
“For example, the functional connectivity between two regions with known (or presumed) structural connections can increase or decrease as a function of several variables, including task performance [103], motivation [104], and emotion [105].”
BackgroundSelf-citationRisold, P., Thompson, R. H., & Swanson, L. W. (1997) · Brain Research Reviews · doi:10.1016/s0165-0173(97)00007-6 · Cited by 347 · cited 2× · see citing works
“The hypothalamus is probably the largest source of nonthalamic direct input to cortex, as reviewed in detail by Larry Swanson and colleagues [29,83].”
BackgroundDefault Mode of Brain Function in Monkeys
Mantini, D., Gerits, A., Nelissen, K., Durand, J., Joly, O., Simone, L., Sawamura, H., Wardak, C., Orban, G. A., Buckner, R. L., et al. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.2318-11.2011 · Cited by 337 · see citing works
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“, regions of high connectivity] into a rich club suggests that the communication hubs of the brain do not operate as individual entities, but instead act as a strongly interlinked collective” (see also [37]).”
BackgroundThe Cognitive-Emotional Brain: From Interactions to Integration
Pessoa, L. (2013) · doi:10.7551/mitpress/9780262019569.001.0001 · Cited by 331 · cited 4× · see citing works
“For instance, we could describe the amygdala as emotional given its contributions to fear conditioning, and the dorsal-medial PFC as cognitive given its role in the processing of response conflict [2].”
BackgroundMethodInfluentialSelf-citationBasic neural mechanisms in behavior.
Lashley, K. S. (1930) · Psychological Review · doi:10.1037/h0074134 · Cited by 328 · see citing works
Romanski, L. M., Giguere, M., Bates, J. F., & Goldman-Rakic, P. S. (1997) · The Journal of Comparative Neurology · doi:10.1002/(sici)1096-9861(19970317)379:3 · Cited by 325 · see citing works
Diverse thalamic projections to the prefrontal cortex in the rhesus monkey
Barbas, H., Henion, T. H. H., & Dermon, C. R. (1991) · Journal of Comparative Neurology · doi:10.1002/cne.903130106 · Cited by 292 · cited 1× · see citing works
“Notably, many extensive fronto-parietal cortical connections are mirrored by overlapping fields in the pulvinar [72,73]: where regions in frontal and parietal cortex are interconnected in the cortex, their projection sites in the pulvinar typically coincide (and the connections are bidirectional between pulvinar and c…”
BackgroundThe primate pulvinar nuclei: vision and action
Grieve, K. L., Acuña, C., & Cudeiro, J. (2000) · Trends in Neurosciences · doi:10.1016/s0166-2236(99)01482-4 · Cited by 290 · cited 1× · see citing works
“The pulvinar complex, as this set of related nuclei is sometimes called, is the largest nuclear mass in the primate thalamus and thought to have expanded in size as it evolved in primates [68,69].”
BackgroundMeta-analytic clustering of the insular cortex
Cauda, F., Costa, T., Torta, D. M. E., Sacco, K., D’Agata, F., Duca, S., Geminiani, G. C., Fox, P. T., & Vercelli, A. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.04.012 · Cited by 289 · see citing works
Network architecture of the long-distance pathways in the macaque brain
Modha, D. S., & Singh, R. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1008054107 · Cited by 283 · cited 8× · see citing works
“Furthermore, in the network analysis by Modha and Singh [34] discussed previously, several amygdala nuclei (e.”
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“Another illustration is given by a study of patients with multiple sclerosis, a pathology that compromises central white matter in a diffuse manner [101].”
BackgroundFunctional ontologies for cognition: The systematic definition of structure and function
Price, C. J., & Friston, K. J. (2004) · Cognitive Neuropsychology · doi:10.1080/02643290442000095 · Cited by 277 · cited 2× · see citing works
“For instance, the left posterior fusiform gyrus in temporal cortex, which has been implicated in the processing of word forms, animal structures, and so on, can be described by a single, more abstract label of “sensori-motor integration” [8].”
BackgroundBeyond the Tripartite Cognition–Emotion–Interoception Model of the Human Insular Cortex
Uddin, L. Q., Kinnison, J., Pessoa, L., & Anderson, M. L. (2014) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00462 · Cited by 275 · see citing works
Self-citationRobinson, J. L., Laird, A. R., Glahn, D. C., Blangero, J., Sanghera, M. K., Pessoa, L., Fox, P. M., Uecker, A. M., Friehs, G. M., Young, K. A., et al. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.12.010 · Cited by 265 · see citing works
Self-citationCorticocentric myopia: old bias in new cognitive sciences
Parvizi, J. (2009) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2009.04.008 · Cited by 260 · cited 1× · see citing works
“Indeed, the idea of cortical inhibition of subcortex has a long history dating to early researchers, such as Hughlings–Jackson (see [85]).”
BackgroundA report of the functional connectivity workshop, Dusseldorf 2002
Lee, L., Harrison, L. M., & Mechelli, A. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00062-4 · Cited by 231 · cited 1× · see citing works
“However, the boundary between anatomy and function becomes blurred very quickly once one starts considering factors that characterize the anatomy [94].”
BackgroundThe relation of ongoing brain activity, evoked neural responses, and cognition
Sadaghiani, S. (2010) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2010.00020 · Cited by 225 · see citing works
Sarter, M. F., Berntson, G. G., & Cacioppo, J. T. (1996) · American Psychologist · doi:10.1037//0003-066x.51.1.13 · Cited by 221 · see citing works
Causal effect of disconnection lesions on interhemispheric functional connectivity in rhesus monkeys
O’Reilly, J. X., Croxson, P. L., Jbabdi, S., Sallet, J., Noonan, M. P., Mars, R. B., Browning, P. G. F., Wilson, C. R. E., Mitchell, A. S., Miller, K. L., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1305062110 · Cited by 220 · cited 2× · see citing works
“In the patients, functional connectivity increased in the face of a concomitant reduction of anatomical connectivity (see also [102]).”
BackgroundAdachi, Y., Osada, T., Sporns, O., Watanabe, T., Matsui, T., Miyamoto, K., & Miyashita, Y. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhr234 · Cited by 211 · cited 1× · see citing works
“[115] compared existing data on structural connectivity in macaques (data collated in the CoComac database) and functional connectivity obtained during MRI scanning of macaques under anesthesia.”
ResultHierarchical functional modularity in the resting‐state human brain
Ferrarini, L., Veer, I. M., Baerends, E., van Tol, M., Renken, R. J., van der Wee, N. J. A., Veltman, D. J., Aleman, A., Zitman, F. G., Penninx, B. W. J. H., et al. (2008) · Human Brain Mapping · doi:10.1002/hbm.20663 · Cited by 200 · cited 1× · see citing works
“Nevertheless, I believe that insisting on a non-overlapping partitioning scheme provides a poor characterization of brain organization (see [142, 143]).”
BackgroundAnalysis of Connectivity: Neural Systems in the Cerebral Cortex
Young, M. P., Scanneil, J. W., Burns, G., & Blakemore, C. B. (1994) · Reviews in the Neurosciences · doi:10.1515/revneuro.1994.5.3.227 · Cited by 189 · cited 3× · see citing works
“The amygdala receives highly processed sensory information [21,78], which is important for value representation since it often depends not on superficial sensory properties, but on those showing some “invariance.”
BackgroundMethodNatural Scenes Viewing Alters the Dynamics of Functional Connectivity in the Human Brain
Betti, V., Penna, S. D., de Pasquale, F., Mantini, D., Marzetti, L., Romani, G. L., & Corbetta, M. (2013) · Neuron · doi:10.1016/j.neuron.2013.06.022 · Cited by 183 · see citing works
Describing functional diversity of brain regions and brain networks
Anderson, M. L., Kinnison, J., & Pessoa, L. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.01.071 · Cited by 182 · cited 2× · see citing works
“Recently, we employed a data-driven approach to investigate the functional repertoire of brain regions based on a large set of functional MRI studies [154].”
BackgroundMethodSelf-citationIndeterminate Organization of the Visual System
Hilgetag, C. C., O’Neill, M. A., & Young, M. P. (1996) · Science · doi:10.1126/science.271.5250.776 · Cited by 174 · cited 1× · see citing works
“Based on these assumptions, Hilgetag and colleagues [149] investigated the organization of the visual system and concluded that “the information in the anatomical constraints cannot be expressed satisfactorily by any single hierarchical ordering” [149].”
BackgroundCognitive neuroscience 2.0: building a cumulative science of human brain function
Yarkoni, T., Poldrack, R. A., Van Essen, D. C., & Wager, T. D. (2010) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2010.08.004 · Cited by 174 · cited 1× · see citing works
“Although this introduces outstanding problems, the availability of data repositories containing the results of thousands of neuroimaging studies provides novel opportunities for the investigation of human brain function [153].”
BackgroundIntact Bilateral Resting-State Networks in the Absence of the Corpus Callosum
Tyszka, J. M., Kennedy, D. P., Adolphs, R., & Paul, L. K. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.1453-11.2011 · Cited by 167 · cited 1× · see citing works
“A striking example of structure-function dissociation was reported by Tyszka and colleagues [114] who investigated an unusual population of adults without the corpus callosum, which provides the major communication pathway between the two hemispheres.”
BackgroundSarter, M. F., Berntson, G. G., & Cacioppo, J. T. (1996) · American Psychologist · doi:10.1037/0003-066x.51.1.13 · Cited by 162 · cited 1× · see citing works
“One way to restate the discussion thus far is to consider psychological events (for instance, “functions”, “behaviors”) and physiological events (for instance, brain regions), which can be denoted Ψ and φ, respectively [9].”
BackgroundThe Amygdala and Its Place in the Cerebral Hemisphere
Swanson, L. W. (2003) · Annals of the New York Academy of Sciences · doi:10.1111/j.1749-6632.2003.tb07081.x · Cited by 161 · cited 1× · see citing works
“Based on the available data at the time, analysis of amygdala pathways by Young and colleagues [21] revealed that, of the 72 cortical areas included in their study, it was connected to all but eight (see also [27,77]).”
MethodNetwork Analysis Reveals Increased Integration during Emotional and Motivational Processing
Kinnison, J., Padmala, S., Choi, J.-M., & Pessoa, L. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.0821-12.2012 · Cited by 153 · cited 2× · see citing works
“In a recent study, we sought instead to understand the network properties of a focused set of brain regions during task conditions engaging them [124].”
BackgroundSelf-citationInferring functional connections between neurons
Stevenson, I. H., Rebesco, J. M., Miller, L. E., & Kording, K. P. (2008) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2008.11.005 · Cited by 150 · cited 1× · see citing works
“Functional connectivity is at times contrasted with effective connectivity, which attempts to explain the origins of the observed functional relationship and, by definition, assumes a model [99].”
BackgroundDynamics of activity and connectivity in physiological neuronal networks
Aertsen, A. M. H. J., & Preissl, H. T. (1991) · MPG.PuRe (Max Planck Society) · Cited by 148 · see citing works
Paradoxical False Memory for Objects After Brain Damage
McTighe, S. M., Cowell, R. A., Winters, B. D., Bussey, T. J., & Saksida, L. M. (2010) · Science · doi:10.1126/science.1194780 · Cited by 145 · cited 1× · see citing works
“Given this type of organization, patterns of impairment in perceptual and memory functions following brain damage reflect the demand that each task places (at specific brain locations) rather than dissociable cognitive modules [14,15].”
BackgroundStereological analysis of the rat and monkey amygdala
Chareyron, L. J., Lavenex, P. B., Amaral, D. G., & Lavenex, P. (2011) · The Journal of Comparative Neurology · doi:10.1002/cne.22677 · Cited by 137 · cited 1× · see citing works
“Chareyron and colleagues [89] found that the lateral, basal, and accessory basal subregions are dramatically more “developed” in monkeys than in rats (based on morphological characteristics, such as cell counts and the volume of subregions).”
BackgroundImpact of state anxiety on the interaction between threat monitoring and cognition
Choi, J. M., Padmala, S., & Pessoa, L. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.08.102 · Cited by 137 · cited 1× · see citing works
“In the emotion task [125], participants viewed an initial cue that determined whether they were in a threat or safe trial; in the motivation task [104], they viewed an initial cue that indicated whether they were in a reward or control trial.”
BackgroundSelf-citationThe Statistical Neuroanatomy of Frontal Networks in the Macaque
Averbeck, B. B., & Seo, M. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000050 · Cited by 112 · cited 5× · see citing works
“Averbeck and Seo [38] proposed an interesting strategy to tackle this problem.”
BackgroundResultInfluentialCognitive ontologies for neuropsychiatric phenomics research
Bilder, R. M., Sabb, F. W., Parker, D. S., Kalar, D. J., Chu, W. W., Fox, J., Freimer, N. B., & Poldrack, R. A. (2009) · Cognitive Neuropsychiatry · doi:10.1080/13546800902787180 · Cited by 109 · cited 1× · see citing works
“How should one define the domain structure? One hope is that cognitive ontologies can be defined that meaningfully carve the “mental” into stable categories [8,166].”
BackgroundChanges in cognitive state alter human functional brain networks
Moussa, M. N., Vechlekar, C. D., Burdette, J. H., Steen, M. R., Hugenschmidt, C. E., & Laurienti, P. J. (2011) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2011.00083 · Cited by 99 · see citing works
New test for the multivariate two-sample problem based on the concept of minimum energy
Aslan, B., & Zech, G. (2005) · Journal of Statistical Computation and Simulation · doi:10.1080/00949650410001661440 · Cited by 91 · cited 1× · see citing works
“To contrast brain networks to each other in terms of the functional fingerprints of the component regions, we employed a multivariate test based on “statistical energy” [161].”
MethodA mathematical approach to the connectivity between the cortical visual areas of the macaque monkey
Jouve, B. (1998) · Cerebral Cortex · doi:10.1093/cercor/8.1.28 · Cited by 83 · cited 1× · see citing works
“A few years later, Jouve and colleagues [41] updated the data set analyzed by Felleman and Van Essen and revised those figures to 37% (observed) and 58% (predicted).”
BackgroundBarger, N., Stefanacci, L., & Semendeferi, K. (2007) · American Journal of Physical Anthropology · doi:10.1002/ajpa.20684 · Cited by 79 · cited 1× · see citing works
“Work by Barger and colleagues [91] have shown that the lateral nucleus of the amygdala in humans is significantly larger than predicted for an ape of human brain size.”
BackgroundCowell, R. A., Bussey, T. J., & Saksida, L. M. (2009) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2009.21373 · Cited by 70 · cited 1× · see citing works
“Given this type of organization, patterns of impairment in perceptual and memory functions following brain damage reflect the demand that each task places (at specific brain locations) rather than dissociable cognitive modules [14,15].”
BackgroundChalfin, B. P., Cheung, D. T., Muniz, J. A. P. C., de Lima Silveira, L. C., & Finlay, B. L. (2007) · Journal of Comparative Neurology · doi:10.1002/cne.21406 · Cited by 61 · cited 1× · see citing works
“The pulvinar complex, as this set of related nuclei is sometimes called, is the largest nuclear mass in the primate thalamus and thought to have expanded in size as it evolved in primates [68,69].”
BackgroundAffective learning enhances activity and functional connectivity in early visual cortex
Damaraju, E., Huang, Y.-M., Barrett, L. F., & Pessoa, L. (2009) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2009.04.023 · Cited by 53 · cited 1× · see citing works
“In one study, the functional connectivity pattern between early visual areas was investigated during affective and neutral contexts [106].”
BackgroundSelf-citationStepniewska, I. (2003) · Frontiers in neuroscience · doi:10.1201/9780203507599.ch3 · Cited by 42 · cited 1× · see citing works
“For example, all twenty to thirty known visual cortical areas connect with the pulvinar, sometimes in a relatively topographic fashion [70,71].”
BackgroundBeyond Statistical Significance: Implications of Network Structure on Neuronal Activity
Vlachos, I., Aertsen, A., & Kumar, A. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002311 · Cited by 25 · cited 4× · see citing works
“Here, I build upon a recent discussion by Vlachos and colleagues [128], who considered this question in the context of neurons.”
BackgroundInfluentialRempel-Clower, N. L., & Barbas, H. (1998) · The Journal of Comparative Neurology · doi:10.1002/(sici)1096-9861(19980831)398:3
Basser (2000) · doi:10.1002/1522-2594(200010)44:4
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Cited by
Sorted by citations
Demystifying cognitive flexibility: Implications for clinical and developmental neuroscience
Dajani, D. R., & Uddin, L. Q. (2015) · Trends in Neurosciences · doi:10.1016/j.tins.2015.07.003 · Cited by 1,046 · see citing works
Small-World Brain Networks Revisited
Bassett, D. S., & Bullmore, E. T. (2016) · The Neuroscientist · doi:10.1177/1073858416667720 · Cited by 847 · see citing works
“…of nervous systems since 2006, as evidenced by rapid growth in research articles, reviews and citations related to“brain graphs” and “connectomes” [20–22]; by the publication of several textbooks [23, 24]; and by the recent launch of new specialist journals for network neuroscience [25].”
BackgroundDynamic reconfiguration of frontal brain networks during executive cognition in humans
Braun, U., Schäfer, A., Walter, H., Erk, S., Romanczuk-Seiferth, N., Haddad, L., Schweiger, J. I., Grimm, O., Heinz, A., Tost, H., et al. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1422487112 · Cited by 791 · see citing works
Farahani, F. V., Karwowski, W., & Lighthall, N. R. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00585 · Cited by 719 · see citing works
“…approaches have opened new avenues toward studying the neural mechanisms underlying human cognition and behavior from the view of interregional brain interactions (Park and Friston, 2013; Pessoa, 2014; Sporns, 2014; Medaglia et al., 2015; Petersen and Sporns, 2015; Kriegeskorte and Douglas, 2018).”
BackgroundLutz, A., Jha, A. P., Dunne, J. D., & Saron, C. D. (2015) · American Psychologist · doi:10.1037/a0039585 · Cited by 697 · see citing works
“…these phenomenological dimensions and activity in specific brain regions is plausible because studies concerning emotion and cognition have shown that brain regions’ functions are inherently multidimensional, and that structurally different regions can perform the same function (Pessoa, 2014).”
BackgroundTowards a universal taxonomy of macro-scale functional human brain networks
Uddin, L. Q., Yeo, B. T. T., & Spreng, R. N. (2019) · Brain Topography · doi:10.1007/s10548-019-00744-6 · Cited by 683 · see citing works
“One subsystem has been neuro-anatomically referred to as the medial temporal lobe subsystem (Andrews-Hanna et al. 2010, 2014).”
InfluentialDixon, M. L., De La Vega, A., Mills, C., Andrews-Hanna, J., Spreng, R. N., Cole, M. W., & Christoff, K. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1715766115 · Cited by 595 · see citing works
Mocanu, D. C., Mocanu, E., Stone, P., Nguyen, P. H., Gibescu, M., & Liotta, A. (2018) · Nature Communications · doi:10.1038/s41467-018-04316-3 · Cited by 524 · see citing works
“Bycontrast to ANNs, biological neural networks have been demonstrated to have a sparse (rather than dense) topology 4,5 , and also hold other important properties that are instrumental to learning ef fi ciency.”
A Network Model of the Emotional Brain
Pessoa, L. (2017) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2017.03.002 · Cited by 526 · see citing works
Self-citationGrayson, D. S., & Fair, D. A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.01.079 · Cited by 411 · see citing works
“The network's behavior can thus be modeled as a set of properties that emerge from the network's unique global structure and local features (Sporns, 2014).”
BackgroundSmall-world human brain networks: Perspectives and challenges
Liao, X., Vasilakos, A. V., & Yong He, A. (2017) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2017.03.018 · Cited by 431 · see citing works
Cliques and cavities in the human connectome
Sizemore, A. E., Giusti, C., Kahn, A. E., Vettel, J. M., Betzel, R. F., & Bassett, D. S. (2017) · Journal of Computational Neuroscience · doi:10.1007/s10827-017-0672-6 · Cited by 381 · see citing works
“2014), though there are exceptions that give the brain its topological properties such as its small-world architecture (Bassett and Bullmore 2006; Pessoa 2014; Hilgetag and Goulas 2016; Muldoon et al. 2016a; Bassett and Bullmore 2016).”
BackgroundJiang, L., & Zuo, X. (2015) · The Neuroscientist · doi:10.1177/1073858415595004 · Cited by 331 · see citing works
“This implicit graphical methodology offers several advantages in preserving weak connectivity in functional connectomics (Jiang and others 2015b; Pessoa 2014).”
Faskowitz, J., Esfahlani, F. Z., Jo, Y., Sporns, O., & Betzel, R. F. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-00719-y · Cited by 323 · see citing works
Beyond the Tripartite Cognition–Emotion–Interoception Model of the Human Insular Cortex
Uddin, L. Q., Kinnison, J., Pessoa, L., & Anderson, M. L. (2014) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00462 · Cited by 275 · see citing works
Self-citationUnderstanding the behavioural consequences of noninvasive brain stimulation.
Bestmann, S., de Berker, A. O., & Bonaiuto, J. (2015) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2014.10.003 · Cited by 255 · see citing works
Masouleh, S. K., Eickhoff, S. B., Hoffstaedter, F., Genon, S., & Initiative, A. D. N. (2019) · eLife · doi:10.7554/elife.43464 · Cited by 231 · see citing works
“Following this philosophical segregation between psychological sciences and neurosciences, it is now widely acknowledged that there is no one-to-one mapping between behavioral functions and brain regions (Anderson, 2016; Genon et al., 2018; Pessoa, 2014).”
Linking interindividual variability in brain structure to behaviour
Genon, S., Eickhoff, S. B., & Masouleh, S. K. (2022) · Nature reviews. Neuroscience · doi:10.1038/s41583-022-00584-7 · Cited by 193 · see citing works
Basic Emotions in Human Neuroscience: Neuroimaging and Beyond
Celeghin, A., Diano, M., Bagnis, A., Viola, M., & Tamietto, M. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.01432 · Cited by 180 · see citing works
“However, it is becoming increasingly clear that the correspondence between brain structure and function is better represented by a oneto-many relationship, or pluripotentiality (Gallese and Lakoff, 2005; Dehaene and Cohen, 2007; Gallese, 2008; Hurley, 2008; Pessoa, 2008, 2014; Anderson, 2016).”
BackgroundSprooten, E., Rasgon, A., Goodman, M. C., Carlin, A., Leibu, E., Lee, W. H., & Frangou, S. (2017) · Human Brain Mapping · doi:10.1002/hbm.23486 · Cited by 180 · see citing works
“However, the degree to which mental processes engage specific, common or partially overlapping regions remains a topic of debate [Pessoa, 2014; Price and Friston, 2005].”
BackgroundJaniri, D., Moser, D. A., Doucet, G. E., Luber, M. J., Rasgon, A., Lee, W. H., Murrough, J. W., Sani, G., Eickhoff, S. B., & Frangou, S. (2020) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2019.3351 · Cited by 173 · see citing works
Nomi, J. S., Farrant, K., Damaraju, E., Rachakonda, S., Calhoun, V. D., & Uddin, L. Q. (2016) · Human Brain Mapping · doi:10.1002/hbm.23135 · Cited by 175 · see citing works
“These network approaches to brain function have recently dominated the cognitive neuroscience landscape, and are continuing to provide more nuanced views of structure-function relationships in the human brain [Pessoa, 2014].”
BackgroundHasson, U., Egidi, G., Marelli, M., & Willems, R. M. (2018) · Cognition · doi:10.1016/j.cognition.2018.06.018 · Cited by 157 · see citing works
“In a conceptual review of functional networks, Pessoa (2014) outlined the foundations for such a vocabulary.”
ALE meta‐analysis reveals dissociable networks for affective and discriminative aspects of touch
Morrison, I. (2016) · Human Brain Mapping · doi:10.1002/hbm.23103 · Cited by 164 · see citing works
“In particular, the posterior-anterior insula axis may contribute to affective evaluation in terms of salience [Menon and Uddin, 2010; Pessoa, 2014], certainty, and/or risk, as has been postulated for the case of pain [Mouraux et al., 2011; Morrison et al., 2013; Perini et al., 2013].”
BackgroundThe embodied brain: towards a radical embodied cognitive neuroscience
Kiverstein, J. D., & Miller, M. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2015.00237 · Cited by 168 · see citing works
“Pessoa has suggested that ‘‘In the extreme, two networks may involve the exact same regions interacting with each other in distinct ways across time’’ (Pessoa, 2014, p. 408).”
BackgroundInfluentialSubcortical contributions to large-scale network communication
Bell, P. T., & Shine, J. M. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.08.036 · Cited by 163 · see citing works
A nice surprise? Predictive processing and the active pursuit of novelty
Clark, A. (2018) · Phenomenology and the Cognitive Sciences · doi:10.1007/s11097-017-9525-z · Cited by 156 · see citing works
“Understanding that role requires us to move beyond what ((Pessoa 2014) p.11) describes as the ‘corticocentric’ image in which evolutionary older sub-cortical structures are dominated and controlled by the more recent cortical overlay.”
BackgroundFace processing in autism spectrum disorders: From brain regions to brain networks
Nomi, J. S., & Uddin, L. Q. (2015) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2015.03.029 · Cited by 155 · see citing works
“…perspective to understanding brain function can provide more parsimonious explanations of the complex relationship between brain and behavior (Pessoa, 2014; Linquist and Barrett, 2012) and in particular can elucidate key principals of functional brain organization underlying typical and…”
BackgroundRichardson, M., McEwan, K., Maratos, F., & Sheffield, D. (2016) · Evolutionary Psychological Science · doi:10.1007/s40806-016-0065-5 · Cited by 155 · see citing works
“However, this approach is not without criticism, and Pessoa (2014) suggests that given its rich connectivity, the amygdala is arguably a processing hub belonging to a minimum of at least three networks pertaining to visual processing, autonomic awareness and the generation of bodily states, and a…”
BackgroundDiano, M., Tamietto, M., Celeghin, A., Weiskrantz, L., Tatu, K., Bagnis, A., Duca, S., Geminiani, G. C., Cauda, F., & Costa, T. (2017) · Scientific Reports · doi:10.1038/srep45260 · Cited by 147 · see citing works
Chronnectomic patterns and neural flexibility underlie executive function
Nomi, J. S., Vij, S. G., Dajani, D. R., Steimke, R., Damaraju, E., Rachakonda, S., Calhoun, V. D., & Uddin, L. Q. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2016.10.026 · Cited by 131 · see citing works
Understanding emotion with brain networks
Pessoa, L. (2017) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2017.09.005 · Cited by 143 · see citing works
Self-citationZhang, H., Chen, X., Shi, F., Li, G., Kim, M., Giannakopoulos, P., Haller, S., & Shen, D. G. (2016) · Journal of Alzheimer s Disease · doi:10.3233/jad-160092 · Cited by 140 · see citing works
“However, after regressing out the task evoked BOLD responses, the data was suitable for FC analysis, where the patterns of FC were proven to be comparable to those in conventional rs-fMRI studies [52] (see Supplementary Material 2 for details).”
InfluentialHappily entangled: prediction, emotion, and the embodied mind
Miller, M., & Clark, A. (2018) · Synthese · doi:10.1007/s11229-017-1399-7 · Cited by 114 · see citing works
“…that target cortical regions either directly or via the thalamus, including areas such as the basal forebrain (Dunnett et al., 1991), hypothalamus (Pessoa, 2014), basal ganglia (Clarke et al., 2008), amygdala (Pessoa, 2013), cerebellum (Leiner et al., 1986), and brainstem via dopaminergic and…”
BackgroundInfluentialIndividual differences and time-varying features of modular brain architecture
Liao, X., Cao, M., Xia, M., & Yong He, A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.02.066 · Cited by 117 · see citing works
Najafi, M., McMenamin, B. W., Simon, J. Z., & Pessoa, L. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.04.054 · Cited by 110 · see citing works
Self-citationControversies and progress on standardization of large-scale brain network nomenclature
Uddin, L. Q., Betzel, R. F., Cohen, J. R., Damoiseaux, J. S., Brigard, F. D., Eickhoff, S. B., Fornito, A., Gratton, C., Gordon, E. M., Laird, A. R., et al. (2023) · Network Neuroscience · doi:10.1162/netn_a_00323 · Cited by 119 · see citing works
“Likewise, hub regions in the brain are thought to dynamically affiliate with disparate clusters of brain regions in a contextdependent fashion (Cole et al., 2013; Pessoa, 2014).”
BackgroundSelf-citationRDoC-based categorization of amygdala functions and its implications in autism
Hennessey, T., Andari, E., & Rainnie, D. G. (2018) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.04.007 · Cited by 105 · see citing works
“…is a prime example of how neuroscience has shifted from a phrenological perspective mapping one function—fear—to one brain region and towards a network paradigm where actions arise from a dynamic affiliation of neural assemblages communicating with one another (Pessoa, 2014; Weiskrantz, 1956).”
Pessoa, L., Medina, L., Hof, P. R., & Desfilis, E. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.09.021 · Cited by 105 · see citing works
“Specific regions do not work in isolation but are part of large-scale connectional systems that support a rich repertoire of functions (Pessoa, 2014).”
BackgroundSelf-citationThe functional overlap of executive control and language processing in bilinguals
Coderre, E. L., Smith, J. F., van Heuven, W. J. B., & Horwitz, B. (2015) · Bilingualism Language and Cognition · doi:10.1017/s1366728915000188 · Cited by 102 · see citing works
“See Pessoa, 2014 and Horwitz, 2014 for further discussion of brain networks.”
BackgroundRefocusing neuroscience: moving away from mental categories and towards complex behaviours
Pessoa, L., Medina, L. M., & Desfilis, E. (2021) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2020.0534 · Cited by 101 · see citing works
Self-citationEarly human brain development: Starring the subplate
Hadders-Algra, M. (2018) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.06.017 · Cited by 100 · see citing works
“2; Modha and Singh, 2010; Pessoa, 2014).”
InfluentialVenkatesh, M., JáJá, J. F., & Pessoa, L. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116398 · Cited by 96 · see citing works
Self-citationLi, H., Satterthwaite, T. D., & Yong Fan, A. (2018) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2018.8363532 · Cited by 95 · see citing works
“On the other hand, datadriven brain decomposition methods have provided alternative tools for charactering intrinsic connectivity networks (ICNs) and estimate functional network connectivity and are favored for modeling many-to-many mapping between brain regions and functions [11].”
MethodA contextualist approach to functional localization in the brain
Burnston, D. C. (2016) · Biology & Philosophy · doi:10.1007/s10539-016-9526-2 · Cited by 98 · see citing works
“MT, for instance, can be said to represent at least motion, coarse depth, and fine depth depending on the stimulus context, and to respond to color when that information helps segment a moving stimulus. Read in this way, there is ample evidence that decomposition can be met. I will here briefly compare current physiol…”
BackgroundResultInfluentialJiang, Y., Li, S., Li, X., Zhang, Y., Chen, Y., Jiang, S., Hou, C., Yao, D., Wang, X., & Luo, C. (2019) · Human Brain Mapping · doi:10.1002/hbm.24584 · Cited by 84 · see citing works
“, 2013), and many-to-many (Pessoa, 2014) have not been fully explored yet.”
BackgroundMicrofluidics for Neuronal Cell and Circuit Engineering
Habibey, R., Arias, J. E. R., Striebel, J., & Busskamp, V. (2022) · Chemical Reviews · doi:10.1021/acs.chemrev.2c00212 · Cited by 86 · see citing works
Précis on <i>The Cognitive-Emotional Brain</i>
Pessoa, L. (2015) · Behavioral and Brain Sciences · doi:10.1017/s0140525x14000120 · Cited by 84 · see citing works
Self-citationA topological insight into restricted Boltzmann machines
Mocanu, D. C., Mocanu, E., Nguyen, P. H., Gibescu, M., & Liotta, A. (2016) · Machine Learning · doi:10.1007/s10994-016-5570-z · Cited by 81 · see citing works
“Lately, the neural networks of the human brain have started to be studied using tools from network science (Pessoa, 2014).”
BackgroundCellular and Molecular Mechanisms Linking Human Cortical Development and Evolution
Libé-Philippot, B., & Vanderhaeghen, P. (2021) · Annual Review of Genetics · doi:10.1146/annurev-genet-071719-020705 · Cited by 78 · see citing works
Large-scale sparse functional networks from resting state fMRI
Li, H.-M., Satterthwaite, T., & Fan, Y. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.05.004 · Cited by 87 · see citing works
“overlap between FNs obtained by the proposed method, indicating that certain brain regions might play multiple roles in the brain networks, especially higher-order association cortex within the frontal and temporal lobes (Pessoa, 2014).”
Individual‐level brain morphological similarity networks: Current methodologies and applications
Cai, M., Ma, J., Wang, Z., Zhao, Y., Zhang, Y., Wang, H., Xue, H., Chen, Y., Zhang, Y., Wang, C., et al. (2023) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.14384 · Cited by 77 · see citing works
Subcortical-cortical dynamical states of the human brain and their breakdown in stroke
Favaretto, C., Allegra, M., Deco, G., Metcalf, N. V., Griffis, J. C., Shulman, G. L., Brovelli, A., & Corbetta, M. (2022) · Nature Communications · doi:10.1038/s41467-022-32304-1 · Cited by 72 · see citing works
Xu, J., Potenza, M. N., Calhoun, V. D., Zhang, R., Yip, S. W., Wall, J. T., Pearlson, G. D., Worhunsky, P. D., Garrison, K. A., & Moran, J. M. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.08.035 · Cited by 68 · see citing works
“This GLM approach and its findings are in general consistent with a modular view of brain functional organization that different mental processes operate in different brain regions (Donoso et al., 2014; Kanwisher, 2010; Pessoa, 2014; Rowland and Moser, 2014; Szentagothai, 1983).”
ResultActivation network mapping for integration of heterogeneous fMRI findings
Peng, S., Xu, P., Jiang, Y., & Gong, G. (2022) · Nature Human Behaviour · doi:10.1038/s41562-022-01371-1 · Cited by 68 · see citing works
Effects of virtual reality-based motor rehabilitation: a systematic review of fMRI studies
Feitosa, J. A., Fernandes, C. A., Casseb, R. F., & Castellano, G. (2021) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac456e · Cited by 69 · see citing works
Hidalgo‐Lopez, E., Mueller, K., Harris, T., Aichhorn, M., Sacher, J., & Pletzer, B. A. (2020) · Brain Structure and Function · doi:10.1007/s00429-019-02019-z · Cited by 66 · see citing works
“Despite the complex relation between structural and functional connectivity (Pessoa 2014), given the acute trophic effects on dendritic spine density and consequent synapse formation, these effects would also be expected to reflect on brain function and connectivity (Kitamura et al.”
Bioinspired nanofluidic iontronics for brain-like computing
Yu, L., Li, X., Luo, C., Lei, Z., Wang, Y., Hou, Y., Wang, M., & Hou, X. (2023) · Nano Research · doi:10.1007/s12274-023-5900-y · Cited by 64 · see citing works
Brain network characterization of high-risk preterm-born school-age children
Fischi-Gómez, E., Muñoz‐Moreno, E., Vasung, L., Griffa, A., Borradori-Tolsa, C., Monnier, M., Lazeyras, F., Thiran, J., & Hüppi, P. S. (2016) · NeuroImage Clinical · doi:10.1016/j.nicl.2016.02.001 · Cited by 64 · see citing works
The Kantian brain: brain dynamics from a neurophenomenological perspective
Fazelpour, S., & Thompson, E. T. (2014) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2014.12.006 · Cited by 61 · see citing works
Individual differences in valence bias: fMRI evidence of the initial negativity hypothesis
Petro, N. M., Tong, T. T., Henley, D. J., & Neta, M. (2018) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsy049 · Cited by 58 · see citing works
“Indeed, it has been demonstrated that one single area may not be explicative of the cognitive functions underlying the processing of a stimulus, instead the strength of the connections may vary and be more informative (Pessoa, 2014; Diano et al., 2017).”
BackgroundCortical thickness patterns as state biomarker of anorexia nervosa
Lavagnino, L., Mwangi, B., Cao, B., Shott, M. E., Soares, J. C., & Frank, G. (2018) · International Journal of Eating Disorders · doi:10.1002/eat.22828 · Cited by 60 · see citing works
“Brain organization refers to how brain regions form networks, and larger or smaller brain regions therefore contribute differently to larger networks that are thought to drive behavior (Pessoa, 2014).”
BackgroundBrucar, L. R., Feczko, E., Fair, D. A., & Zilverstand, A. (2022) · Biological Psychiatry · doi:10.1016/j.biopsych.2022.12.020 · Cited by 59 · see citing works
Psychiatric sequelae of traumatic brain injury — future directions in research
Li, L. M., Carson, A. J., & Dams-O’Connor, K. (2023) · Nature Reviews Neurology · doi:10.1038/s41582-023-00853-8 · Cited by 57 · see citing works
The diversity and multiplexity of edge communities within and between brain systems
Jo, Y., Esfahlani, F. Z., Faskowitz, J., Chumin, E. J., Sporns, O., & Betzel, R. F. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.110032 · Cited by 58 · see citing works
Di, X., Huang, J., & Biswal, B. B. (2016) · Brain Structure and Function · doi:10.1007/s00429-016-1239-4 · Cited by 57 · see citing works
“Therefore, it is not a one-to-one mapping between function and connectivity (Pessoa 2014).”
BackgroundA functorial Dowker theorem and persistent homology of asymmetric networks
Chowdhury, S., & Mémoli, F. (2018) · Journal of Applied and Computational Topology · doi:10.1007/s41468-018-0020-6 · Cited by 57 · see citing works
“…2010), commerce and economy (Elliott et al. 2014; Easley and Kleinberg 2010; Acemoglu et al. 2015), neuroscience (Sporns 2011, 2012; Sporns and Kötter 2004; Rubinov and Sporns 2010; Pessoa 2014), biology (Barabási and Oltvai 2004; Huson et al. 2010), and defence (Masys 2014), to name a few sources.”
BackgroundConnectivity‐based parcellation of normal and anatomically distorted human cerebral cortex
Doyen, S., Nicholas, P. J., Poologaindran, A., Crawford, L. S., Young, I. M., Romero-García, R., & Sughrue, M. E. (2021) · Human Brain Mapping · doi:10.1002/hbm.25728 · Cited by 56 · see citing works
“A unifying principle of brain network organization is that the functional relevance of a brain area is dependent on its connectivity with surrounding brain areas (Fischl, 2012; McIntosh, 2004; Pessoa, 2014).”
BackgroundSurlari, Z., Budală, D. G., Lupu, I. C., Stelea, C. G., Butnaru, O., & Luchian, I. A. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12237378 · Cited by 55 · see citing works
“The human brain can be conceptualized as a complex network of interconnected neurons that communicate with one another, transmitting electrical impulses throughout the entire body [2].”
BackgroundClosing the mechanistic gap: the value of microarchitecture in understanding cognitive networks
Paquola, C., Amunts, K., Evans, A. C., Smallwood, J., & Bernhardt, B. C. (2022) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2022.07.001 · Cited by 51 · see citing works
Commitment System Theory: The Evolving Structure of Commitments to Multiple Targets
Klein, H. J., Solinger, O. N., & Duflot, V. (2020) · Academy of Management Review · doi:10.5465/amr.2018.0031 · Cited by 58 · see citing works
Holczer, A., Németh, V. L., Vékony, T., Vécsei, L., Klivènyi, P., & Must, A. (2020) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2020.00179 · Cited by 52 · see citing works
“Brain regions organize into brain networks to implement various cognitive and other operations (Pessoa, 2014).”
BackgroundSparse evolutionary deep learning with over one million artificial neurons on commodity hardware
Liu, S., Mocanu, D. C., Matavalam, A. R. R., Pei, Y., & Pechenizkiy, M. (2020) · Neural Computing and Applications · doi:10.1007/s00521-020-05136-7 · Cited by 51 · see citing works
“Sparse evolutionary training Inspired by the fact that biological neural networks are prone to be sparse, rather than dense (Strogatz, 2001; Pessoa, 2014), there is an increasing interest in conceiving neural networks with a sparse topology (Mocanu et al.”
BackgroundCongenital blindness is associated with large-scale reorganization of anatomical networks
Hasson, U., Andric, M., Atılgan, H., & Collignon, O. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.12.048 · Cited by 51 · see citing works
Brain flexibility associated with need for cognition contributes to creative achievement
He, L., Zhuang, K., Li, Y., Sun, J., Meng, J., Zhu, W., Mao, Y., Chen, Q., Chen, X., & Qiu, J. (2019) · Psychophysiology · doi:10.1111/psyp.13464 · Cited by 50 · see citing works
On the interplay between mathematics and biology
Bellomo, N., Elaiw, A. M., Althiabi, A. M., & Alghamdi, M. (2014) · Physics of Life Reviews · doi:10.1016/j.plrev.2014.12.002 · Cited by 50 · see citing works
Tasks activating the default mode network map multiple functional systems
Mancuso, L., Cavuoti-Cabanillas, S., Liloia, D., Manuello, J., Buzi, G., Cauda, F., & Costa, T. (2022) · Brain Structure and Function · doi:10.1007/s00429-022-02467-0 · Cited by 49 · see citing works
“There are several obvious reasons explaining why canonical RSNs are a simplistic representation of brain complexity (Pessoa 2014).”
Building an EEG-fMRI Multi-Modal Brain Graph: A Concurrent EEG-fMRI Study
Yu, Q., Wu, L., Bridwell, D. A., Erhardt, E. B., Du, Y., He, H., Chen, J., Liu, P., Jing Sui (Beijing Normal University), my correct affiliation is beijing normal university, N. Q. U. O. S. A. T., Pearlson, G. D., et al. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00476 · Cited by 49 · see citing works
Affect-biased attention and predictive processing
Ransom, M., Fazelpour, S., Markovic, J., Kryklywy, J. H., Thompson, E. T., & Todd, R. M. (2020) · Cognition · doi:10.1016/j.cognition.2020.104370 · Cited by 45 · see citing works
“For example, they follow (Pessoa, 2014) in viewing the medial pulvinar as amplifying weak but biologically valuable signals and so influencing behavior.”
BackgroundHossein, S., Cooper, J. A., DeVries, B. A. M., Nuutinen, M. R., Hahn, E., Kragel, P. A., & Treadway, M. T. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-02056-5 · Cited by 47 · see citing works
“Within this system, the amygdala has been indicated as a network “ hub ” , given its high connectedness with multiple cortical areas in primates [12, 13].”
BackgroundA connectome-based mechanistic model of focal cortical dysplasia
Hong, S., Lee, H.-M., Gill, R. S., Crane, J., Sziklas, V., Bernhardt, B. C., Bernasconi, N., & Bernasconi, A. (2019) · Brain · doi:10.1093/brain/awz009 · Cited by 45 · see citing works
Reis, J. C., Antoni, M. H., & Travado, L. (2020) · CNS Spectrums · doi:10.1017/s1092852918001621 · Cited by 44 · see citing works
Burrows, C. A., Timpano, K. R., & Uddin, L. Q. (2017) · Clinical Psychological Science · doi:10.1177/2167702616683506 · Cited by 43 · see citing works
“Current conceptualizations of brain function contend that local and distal brain regions are functionally coupled, and operate within networks to achieve specific outcomes (Biswal, 526 Burrows et al. Zerrin Yetkin, Haughton, & Hyde, 1995; Damoiseaux et al., 2006; Pessoa, 2014; Smith et al., 2009).”
BackgroundReliability of graph metrics derived from resting‐state human EEG
Kuntzelman, K. M., & Miskovic, V. (2016) · Psychophysiology · doi:10.1111/psyp.12600 · Cited by 43 · see citing works
Detection of Pilot’s Mental Workload Using a Wireless EEG Headset in Airfield Traffic Pattern Tasks
Liu, C., Zhang, C., Sun, L., Liu, K., Liu, H., Zhu, W., & Jiang, C. (2023) · Entropy · doi:10.3390/e25071035 · Cited by 41 · see citing works
Zhang, J., Lin, X., Fu, G., Sai, L., Chen, H., Wang, M., Wang, M., Liu, Q., Yang, G., Zhang, J., et al. (2016) · Scientific Reports · doi:10.1038/srep25297 · Cited by 40 · see citing works
Emotion and the Interactive Brain: Insights From Comparative Neuroanatomy and Complex Systems
Pessoa, L. (2018) · Emotion Review · doi:10.1177/1754073918765675 · Cited by 58 · see citing works
“From that viewpoint, what is important is not simply the anatomical location of a region but its position in a space of functional relationships to other regions (Aertsen & Preissl, 1991; Friston et al., 1997; Pessoa, 2014).”
BackgroundInfluentialSelf-citationvan Schie, C. C., van Harmelen, A., Hauber, K., Boon, A. E., Crone, E. A., & Elzinga, B. M. (2017) · European Journal of Psychotraumatology · doi:10.1080/20008198.2016.1272788 · Cited by 38 · see citing works
“Finally, as the mirror and mentalization system involve a network of brain regions, we should understand neural findings in the context of a larger network (Bressler & Menon, 2010; Pessoa, 2014).”
Deep Variational Autoencoder for Mapping Functional Brain Networks
Qiang, N., Dong, Q., Ge, F., Liang, H., Ge, B., Zhang, S., Sun, Y., Gao, J., & Liu, T. (2020) · IEEE Transactions on Cognitive and Developmental Systems · doi:10.1109/tcds.2020.3025137 · Cited by 39 · see citing works
Altered brain networks in psychogenic erectile dysfunction: a resting‐state fMRI study
Chen, J., Chen, Y., Chen, G., Dai, Y., Yao, Z., & Lü, Q. (2017) · Andrology · doi:10.1111/andr.12411 · Cited by 38 · see citing works
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Toward an integrative science of social vision in intergroup bias
Bagnis, A., Celeghin, A., Mosso, C. O., & Tamietto, M. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.04.020 · Cited by 36 · see citing works
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“As others have noted, identifying causal links between structural and functional network disturbance is fundamentally difficult (43) and depends crucially on the validity of the measurements and the proposed model (5, 25).”
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“There are numerous lines of evidence to suggest that brain-behavior relationships are not simply one-to-one (Pessoa, 2014).”
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An Efficient Methodology for Brain MRI Classification Based on DWT and Convolutional Neural Network
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“The brain connectivity characterizes networks of brain regions connected by anatomical traits [4,5].”
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- Authors
- Pessoa, L.
- Affiliations
- University of Maryland, College Park (US)
- Corresponding author
- Pessoa, Luiz
- ORCID
- Pessoa, Luiz
- Venue
- Physics of Life Reviews
- Publisher
- Elsevier BV
- Published
- 2014-09
- Volume
- 11
- Issue
- 3
- Pages
- 400-435
- ISSN
- 1571-0645 (ISSN-L)
- PMC
- PMC4157099
- OpenAlex
- W2031461126
- Cited by
- 464
- References
- 156
- Citations by year
- 2026: 31 · 2025: 48 · 2024: 47 · 2023: 59 · 2022: 45 · 2021: 37 · 2020: 31 · 2019: 30 · 2018: 26 · 2017: 35 · 2016: 39 · 2015: 19 · 2014: 16 · 2013: 1
- FWCI
- 3.52
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Physics of Life Reviews (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Institute of Mental Health (R01MH071589)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- brain networks, brain organization, structure-function mapping, brain-behavior relationship, network perspective, many-to-many mapping, community detection, subnetworks, hierarchical brain organization, brain regions
- MeSH terms
- Algorithms, Animals, Brain, Brain Mapping, Humans, Nerve Net
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