Thalamocortical loops as temporal demodulators across senses.

Sensory information is coded in space and in time. The organization of neuronal activity in space maintains straightforward relationships with the spatial organization of the perceived environment. In contrast, the temporal organization of neuronal activity is not trivially related to external features due to sensor motion. Still, the temporal organization shares similar principles across sensory modalities. Likewise, thalamocortical circuits exhibit common features across senses. Focusing on touch, vision, and audition, we review their shared coding principles and suggest that thalamocortical systems include circuits that allow analogous recoding mechanisms in all three senses. These thalamocortical circuits constitute oscillations-based phase-locked loops, that translate temporally-coded sensory information to rate-coded cortical signals, signals that can integrate information across sensory and motor modalities. The loop also allows predictive locking to the onset of future modulations of the sensory signal. The paper thus suggests a theoretical framework in which a common thalamocortical mechanism implements temporal demodulation across senses.

Resting-State Activity in High-Order Visual Areas as a Window into Natural Human Brain Activations.

A major limitation of conventional human brain research has been its basis in highly artificial laboratory experiments. Due to technical constraints, little is known about the nature of cortical activations during ecological real life. We have previously proposed the "spontaneous trait reactivation (STR)" hypothesis arguing that resting-state patterns, which emerge spontaneously in the absence of external stimulus, reflect the statistics of habitual cortical activations during real life. Therefore, these patterns can serve as a window into daily life cortical activity. A straightforward prediction of this hypothesis is that spontaneous patterns should preferentially correlate to patterns generated by naturalistic stimuli compared with artificial ones. Here we targeted high-level category-selective visual areas and tested this prediction by comparing BOLD functional connectivity patterns formed during rest to patterns formed in response to naturalistic stimuli, as well as to more artificial category-selective, dynamic stimuli. Our results revealed a significant correlation between the resting-state patterns and functional connectivity patterns generated by naturalistic stimuli. Furthermore, the correlations to naturalistic stimuli were significantly higher than those found between resting-state patterns and those generated by artificial control stimuli. These findings provide evidence of a stringent link between spontaneous patterns and the activation patterns during natural vision.