The chronoarchitecture of the human brain—natural viewing conditions reveal a time-based anatomy of the brain

Abstract

A dominant tendency in cerebral studies has been the attempt to locate architecturally distinct parts of the cortex and assign special functions to each, through histological, clinical or hypothesis-based imaging experiments. Here we show that the cerebral cortex can also be subdivided into different components temporally, without any a priori hypotheses, based on the principle of functional independence. This states that distinct functional subdivisions have activity time courses (ATCs) that are, if not independent, at least characteristic to each when the brain is exposed to natural conditions. To approach a time-based anatomy experimentally, we recorded whole-brain activity using functional magnetic resonance imaging (fMRI) and analyzed the data with independent component analysis (ICA). Our results show that a multitude of cortical areas can be identified based purely on their characteristic ATCs during natural conditions. We demonstrate that a more 'rich' stimulation (free viewing of a movie) leads to more areas being activated in a specific way than conventional stimuli, allowing for a more detailed dissection of the cortex into its subdivisions. We show that stimulus-driven functionally specialized areas can be identified by intersubject correlation even if their function is unknown. Chronoarchitectonic mapping thus opens the prospect of identifying previously unknown cortical subdivisions based on natural viewing conditions by exploiting the characteristic temporal 'fingerprint' that is unique to each. D

Rapidly acquired multisensory association in the olfactory cortex

“…This method can reveal chronoarchitectonically identified areas or functionally connected regions and generally provides additional information when compared to standard regression‐based fMRI data analyses techniques (Bartels and Zeki 2004; Karunanayaka et al. 2014).…”

Independent components in stimulus-related BOLD signals and estimation of the underlying neural responses

“…The analysis of independent time-locked components can be addressed by applying ICA to the spatial domain, assuming that different neural mechanisms provide statistically independent activations across the voxels and stimulus types. The spatial domain approach was successfully applied in a recent study by Bartels and Zeki (2004), who attempted to resolve different visual areas in the cortex based on the differences of their neural responses to complex visual stimuli (movies). Their approach allowed them to identify different neural mechanisms in the cortex, which in many instances closely corresponded to visual areas established with localizer stimuli.…”

Brain dynamics during natural viewing conditions—A new guide for mapping connectivity in vivo

“…Our findings were confirmed by those of Hasson et al (2004) and go beyond in emphasizing a surprisingly high degree of area-specific activity. Its extent is such that data-driven methods such as independent component analysis (ICA) can identify and segregate a multitude of distinct regions across the whole brain, even within the visual cortex, based solely on their characteristic activity time courses (ATCs) during natural vision (Bartels and Zeki, 2004a). This reveals a highly modular organization of brain function.…”

“…Functional specialization may in part be a consequence of the high independence with which different features vary over time (see the dPrinciple of Functional IndependenceT in Zeki (2003, 2004a,b)). Complex stimulation (such as free viewing) thus leads to more distinct activation in functionally specialized areas, as each processes the features it is specialized for (Bartels and Zeki, 2004a). These considerations are of high relevance for the mapping of connectivity, as the high regional specificity of activation time courses observed during natural viewing should make correlations induced by anatomical connectivity stand out particularly well.…”