From deep brain phenotyping to functional atlasing

TLDR: The concept of functional fingerprint is introduced in this article, which subsumes the accumulation of functional information at a given brain location, which is discussed in detail through concrete examples taken from the Individual Brain Charting dataset.

Abstract: How can neuroimaging inform us about the function of brain structures? This simple question immediately brings out two pertinent issues: (i) an inference problem, namely the fact that the function of a region can only be asserted after observing a large array of experimental conditions or contrasts; and (ii) the fact that the identity of a region can only be defined with accuracy at the individual level, because of intrinsic differences between subjects. To overcome this double challenge, we consider an approach based on the deep phenotyping of behavioral responses from task data acquired using functional Magnetic Resonance Imaging. The concept of functional fingerprint-which subsumes the accumulation of functional information at a given brain location-is herein discussed in detail through concrete examples taken from the Individual Brain Charting dataset.

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Figure 2: Principle of Dictionary Learning A set of 149 contrast images corresponding to distinct contrasts (left) can be factorized into a set of functional profiles multiplied by sparse non-negative topographies (right). This latent-factor data model yields an efficient description of the brain maps used as inputs. The sparsity of the obtained topographies allows for a better characterization of the ensuing networks, while functional profiles yield a precise specification of their functional role. This factorization can be easily extended to multi-subjects settings [VSPT13].

Figure 4: Variability of individual topographies pertaining to task-elicited brain responses. Based on the decomposition of a set of contrast maps in 11 subjects, we define 20 networks through a data-driven procedure. The resulting topographies are mapped on the left and right hemispheres of the cortex. The cross-subject consensus maps are shown at the top-right corner of both panels; they are identical to those displayed on Figure 3. Individual topographies show conspicuous variability across individuals, although the large-scale organization remains consistent.

Figure 1: What is a functional fingerprint? A functional prototype or functional fingerprint is a vector of response to a set of contrasts in a given brain location or brain region. It characterizes the profile of functional response to a possibly wide array of experimental conditions in that particular region. In this example, we observe that the voxel considered obtains large responses to conditions involving sounds and, specifically, voice content.

Figure 3: Identifying suitable network descriptions of the brain. From 149 contrast maps available in 11 subjects, we derive k = 20 networks in a data-driven way. (left) Each network is characterized by its functional connectivity to other networks as well as by a functional signature. The functional signature is summarized by the names of the two contrasts that elicit most activation in that particular network. Using activation or resting-state data, the connectivity among these networks is captured by partial correlations among the regional signals. (right) The networks are also characterized by topographic maps, summarized herein by their cortical representation.