Accessing Real-Life Episodic Information from Minutes versus Hours Earlier Modulates Hippocampal and High-Order Cortical Dynamics.

It is well known that formation of new episodic memories depends on hippocampus, but in real-life settings (e.g., conversation), hippocampal amnesics can utilize information from several minutes earlier. What neural systems outside hippocampus might support this minutes-long retention? In this study, subjects viewed an audiovisual movie continuously for 25 min; another group viewed the movie in 2 parts separated by a 1-day delay. Understanding Part 2 depended on retrieving information from Part 1, and thus hippocampus was required in the day-delay condition. But is hippocampus equally recruited to access the same information from minutes earlier? We show that accessing memories from a few minutes prior elicited less interaction between hippocampus and default mode network (DMN) cortical regions than accessing day-old memories of identical events, suggesting that recent information was available with less reliance on hippocampal retrieval. Moreover, the 2 groups evinced reliable but distinct DMN activity timecourses, reflecting differences in information carried in these regions when Part 1 was recent versus distant. The timecourses converged after 4 min, suggesting a time frame over which the continuous-viewing group may have relied less on hippocampal retrieval. We propose that cortical default mode regions can intrinsically retain real-life episodic information for several minutes.

Temporal scaling of neural responses to compressed and dilated natural speech.

Different brain areas integrate information over different timescales, and this capacity to accumulate information increases from early sensory areas to higher order perceptual and cognitive areas. It is currently unknown whether the timescale capacity of each brain area is fixed or whether it adaptively rescales depending on the rate at which information arrives from the world. Here, using functional MRI, we measured brain responses to an auditory narrative presented at different rates. We asked whether neural responses to slowed (speeded) versions of the narrative could be compressed (stretched) to match neural responses to the original narrative. Temporal rescaling was observed in early auditory regions (which accumulate information over short timescales) as well as linguistic and extra-linguistic brain areas (which can accumulate information over long timescales). The temporal rescaling phenomenon started to break down for stimuli presented at double speed, and intelligibility was also impaired for these stimuli. These data suggest that 1) the rate of neural information processing can be rescaled according to the rate of incoming information, both in early sensory regions as well as in higher order cortexes, and 2) the rescaling of neural dynamics is confined to a range of rates that match the range of behavioral performance.

Predicting human resting-state functional connectivity from structural connectivity.

In the cerebral cortex, the activity levels of neuronal populations are continuously fluctuating. When neuronal activity, as measured using functional MRI (fMRI), is temporally coherent across 2 populations, those populations are said to be functionally connected. Functional connectivity has previously been shown to correlate with structural (anatomical) connectivity patterns at an aggregate level. In the present study we investigate, with the aid of computational modeling, whether systems-level properties of functional networks--including their spatial statistics and their persistence across time--can be accounted for by properties of the underlying anatomical network. We measured resting state functional connectivity (using fMRI) and structural connectivity (using diffusion spectrum imaging tractography) in the same individuals at high resolution. Structural connectivity then provided the couplings for a model of macroscopic cortical dynamics. In both model and data, we observed (i) that strong functional connections commonly exist between regions with no direct structural connection, rendering the inference of structural connectivity from functional connectivity impractical; (ii) that indirect connections and interregional distance accounted for some of the variance in functional connectivity that was unexplained by direct structural connectivity; and (iii) that resting-state functional connectivity exhibits variability within and across both scanning sessions and model runs. These empirical and modeling results demonstrate that although resting state functional connectivity is variable and is frequently present between regions without direct structural linkage, its strength, persistence, and spatial statistics are nevertheless constrained by the large-scale anatomical structure of the human cerebral cortex.