Precision Functional Mapping to Advance Developmental Psychiatry Research

Abstract

Many psychiatric conditions have their roots in early development. Individual differences in prenatal brain function (which is influenced by a combination of genetic risk and the prenatal environment) likely interact with individual differences in postnatal experience, resulting in substantial variation in brain functional organization and development in infancy. Neuroimaging has been a powerful tool for understanding typical and atypical brain function and holds promise for uncovering the neurodevelopmental basis of psychiatric illness; however, its clinical utility has been relatively limited thus far. A substantial challenge in this endeavor is the traditional approach of averaging brain data across groups despite individuals varying in their brain organization, which likely obscures important clinically relevant individual variation. Precision functional mapping (PFM) is a neuroimaging technique that allows the capture of individual-specific and highly reliable functional brain properties. Here, we discuss how PFM, through its focus on individuals, has provided novel insights for understanding brain organization across the life span and its promise in elucidating the neural basis of psychiatric disorders. We first summarize the extant literature on PFM in normative populations, followed by its limited utilization in studying psychiatric conditions in adults. We conclude by discussing the potential for infant PFM in advancing developmental precision psychiatry applications, given that many psychiatric disorders start during early infancy and are associated with changes in individual-specific functional neuroanatomy. By exploring the intersection of PFM, development, and psychiatric research, this article underscores the importance of individualized approaches in unraveling the complexities of brain function and improving clinical outcomes across development.

Keywords: Development; Functional magnetic resonance imaging; Precision neuroimaging; Psychiatry.

Figure 1

Functional network topography is individual specific. Functional networks identified in group-average data (top) and in 2 individuals (bottom). Network variants are highlighted that are observed across individuals but absent from the group average. In the group average, the inferior frontal gyrus belongs to the frontoparietal network (yellow), but an inclusion (green) is shown in MSC01 whereby the dorsal attention network (green) is present on the inferior frontal gyrus. In both individuals, the salience network (black) shows a border shift (black) compared with the group average. [Adapted from Figure 3 in Gordon et al. (32) with permission]. MSC, Midnight Scan Club.

Figure 2

Individual network mapping is required to identify the same functional biological entity across individuals. These maps show the medial prefrontal cortex (mPFC) in 5 individuals scanned using precision functional mapping (PFM). Both panels show the magnitude of resting-state functional connectivity (RSFC) of the mPFC to the default mode network (DMN) subdivision of the amygdala. The white circles in the top panel indicate the same anatomically defined location across all 5 individuals. Note that the magnitude of RSFC within this circle varies substantially across individuals, with some individuals having positive RSFC and others negative RSFC. The colored outlines in the bottom panel indicate network outlines for each individual. Each individual has a consistent pattern of RSFC when considering functional locations, e.g., positive RSFC to portions of the mPFC that are DMN and negative RSFC to portions of the mPFC that are salience network. Standard group-level approaches compare RSFC across individuals in the same anatomical location (the white circle in panel B), confounding variation in RSFC between functional areas with variation in the functional area present at a specific anatomical location. [Adapted from Figure 4B in Sylvester et al. (43) with permission]. MSC, Midnight Scan Club.

Figure 3

Novel applications of precision functional mapping (PFM) for psychiatric research among adolescent and adult populations. (A) PFM can characterize mechanisms of psychiatric illness that result from alterations in particular functionally defined brain areas by allowing for precise measurement of individual-specific functional brain areas and networks, rather than traditional anatomically defined areas. For instance, models of treatment-resistant depression posit altered activity in the subgenual anterior cingulate cortex (sgACC), potentially resulting from impaired regulation by the dorsolateral prefrontal cortex (dlPFC) (white circle), which has different functional definitions across individuals, as shown in this example. Thus, one hypothesis is that the efficacy of transcranial magnetic stimulation could be improved by stimulating the specific portion of the dlPFC with the highest magnitude of negative resting-state functional connectivity (RSFC) with the sgACC (i.e., defining transcranial magnetic stimulation targets based on functional definitions rather than anatomical definitions), given that functional definitions within the dlPFC vary across individuals. (B) PFM can uncover mechanisms that explicitly rely on differences in functional brain organization. In this example from Lynch et al., work using PFM demonstrated that the surface area of the salience network (SN) was 2 times larger in the individuals with major depressive disorder (MDD) than healthy control participants. (C) PFM can detect mechanisms that vary across individuals with the same symptomatically defined disorder. In this example, we demonstrate an individual’s specific pattern of RSFC that correlated with depression symptoms before and after treatment with brexanolone. Such patterns may vary across individuals, which can be detected with PFM. [Adapted from Figure 1A in Lynch et al. (48) (B) and Supplemental Figure 2 in Guard et al. (49) (C), with permission]. DM, Default Mode Network; EPDS, Edinburgh Postnatal Depression Scale; FC, Functional Connectivity; MSC, Midnight Scan Club.

Figure 4

Precision functional mapping (PFM) affords the unique opportunity to test common theories of neurodevelopmental mechanisms of psychiatric disorders. (A) Psychiatric illness may arise due to alterations in the timing of maturation of relevant neural circuits. This example illustrates the maturational trajectory of network A in 2 individuals and how alterations in the typical maturational trajectory can either be in the timing of maturation of network A (when is the change) or the maturational pace (how much change is there). PFM can be useful in characterizing whether alterations in the timing of maturation or the maturational pace of specific neural measures, such as network functional connectivity, relate to expression of psychiatric symptoms. (B) Psychiatric illnesses may emerge as a result of altered neurodevelopmental cascades, in which early neural alterations cause a cascade of altered neurodevelopment later in life. In this example, network A (green) is a typically early maturing network and network B (blue) typically matures later, relying on environmental inputs encoded by network A. Thus, in this example, when network A has an altered maturational trajectory in an infant such that it does not reach its peak maturation level when it is intended to, environmental inputs are improperly encoded, resulting in downstream effects to network B’s maturational trajectory. (C) Psychiatric illnesses may be associated with overall changes in neural plasticity that can influence adaptation of neural circuits to the environment. In this example, we depict that regional plasticity (i.e., measures of plasticity in different brain networks or regions) may vary across development, whereby peaks in plasticity for various brain regions occur at different points in development. PFM can allow for investigations of plasticity and track plasticity of specific brain regions across development to identify when they may be most susceptible to interventions.