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We propose that the preservation of functional integration, estimated from measures of neural synchrony, is a key objective of neurocompensatory mechanisms associated with healthy human ageing. To support this proposal, we demonstrate how phase-locking at the peak alpha frequency in Magnetoencephalography recordings remains invariant over the lifespan in a large cohort of human participants, aged 18-88 years. Using empirically derived connection topologies from diffusion tensor imaging data, we create an in-silico model of whole-brain alpha dynamics. We show that enhancing inter-areal coupling can cancel the effect of increased axonal transmission delays associated with age-related degeneration of white matter tracts, albeit at slower network frequencies. By deriving analytical solutions for simplified connection topologies, we further establish the theoretical principles underlying compensatory network re-organization. Our findings suggest that frequency slowing with age- frequently observed in the alpha band in diverse populations- may be viewed as an epiphenomenon of the underlying compensatory mechanism. Analysis of MEG data from healthy participants and whole-brain network modeling suggests that the brain compensates for age-related disruptions in connectivity by slowing down the frequency of neural synchronization. [ABSTRACT FROM AUTHOR]

Bioluminescence is a chemical phenomenon common in fireflies and aquatic life. A team of MIT engineers has taken the first step towards leveraging this phenomenon using plant nanobionics to create light-emitting trees. These light-emitting trees can serve as our desk lamps or maybe even street lamps in the future. The team has packaged the light-emitting molecules, enzymes, and coenzymes responsible for bioluminescence in living organisms, into nanoparticles and inserted them into plants to perform the chemical reaction, which emits light in the visible region. [ABSTRACT FROM AUTHOR]

Episodic memories are contextual experiences ordered in time. This is underpinned by associative binding between events within the same contexts. The role of prediction errors in declarative memory is well established but has not been investigated in the time dimension of complex episodic memories. Here we combine these two properties of episodic memory, extend them into the temporal domain and demonstrate that prediction errors in different naturalistic contexts lead to changes in the temporal ordering of event structures in them. The wrongly predicted older sequences were weakened despite their reactivation. Interestingly the newly encoded sequences with prediction errors, seen once, showed accuracy as high as control sequences which were viewed repeatedly without change. Drift–diffusion modelling revealed a lower decision threshold for the newer sequences than older sequences, reflected by their faster recall. Moreover, participants' adjustments to their decision threshold significantly correlated with their relative speed of sequence memory recall. These results suggest a temporally distinct and adaptive role for prediction errors in learning and reorganizing episodic temporal sequences. [ABSTRACT FROM AUTHOR]

Multilevel crosstalk as a neural basis for motor control has been widely discussed in the literature. Since no natural process is instantaneous, any crosstalk model should incorporate time delays, which are known to induce temporal coupling between functional elements and stabilize or destabilize a particular mode of coordination. In this article, we systematically study the dynamics of rhythmic bimanual coordination under the influence of varying connection topology as realized by callosal fibers, cortico-thalamic projections, and crossing peripheral fibers. Such connectivity contributes to various degrees of neural crosstalk between the effectors which we continuously parameterize in a mathematical model. We identify the stability regimes of bimanual coordination as a function of the degree of neural crosstalk, movement amplitude and the time delays involved due to signal processing. Prominent examples include explanations of the decreased stability of the antiphase mode of coordination in split brain patients and the role of coupling in mediating bimanual coordination. [ABSTRACT FROM AUTHOR]

Complex protein networks underlie any cellular function. Certain proteins play a pivotal role in many network configurations, disruption of whose expression proves fatal to the cell. An efficient method to tease out such key proteins in a network is still unavailable. Here, we used graph-theoretic measures on protein-protein interaction data (interactome) to extract biophysically relevant information about individual protein regulation and network properties such as formation of function specific modules (sub-networks) of proteins. We took 5 major proteins that are involved in neuronal apoptosis post Chandipura Virus (CHPV) infection as seed proteins in a database to create a meta-network of immediately interacting proteins (1st order network). Graph theoretic measures were employed to rank the proteins in terms of their connectivity and the degree upto which they can be organized into smaller modules (hubs). We repeated the analysis on 2nd order interactome that includes proteins connected directly with proteins of 1st order. FADD and Casp-3 were connected maximally to other proteins in both analyses, thus indicating their importance in neuronal apoptosis. Thus, our analysis provides a blueprint for the detection and validation of protein networks disrupted by viral infections. [ABSTRACT FROM AUTHOR]