Network mechanisms of intentional learning

The ability to learn new tasks rapidly is a prominent characteristic of human behaviour. This ability relies on flex- ible cognitive systems that adapt in order to encode temporary programs for processing non-automated tasks. Previous functional imaging studies have revealed distinct roles for the lateral frontal cortices (LFCs) and the ven- tral striatum in intentional learning processes. However, the human LFCs are complex; they house multiple dis- tinct sub-regions, each of which co-activates with a different functional network. It remains unclear how these LFC networks differ in their functions and how they coordinate with each other, and the ventral striatum, to support intentional learning. Here, we apply a suite of fMRI connectivity methods to determine how LFC networks activate and interact at different stages of two novel tasks, in which arbitrary stimulus-response rules are learnt either from explicit instruction or by trial-and-error. We report that the networks activate en masse and in synchrony when novel rules are being learnt from instruction. However, these networks are not homogeneous in their functions; instead, the directed connectivities between them vary asymmetrically across the learning timecourse and they disengage from the task sequentially along a rostro-caudal axis. Furthermore, when negative feedback indicates the need to switch to alternative stimulus–response rules, there is additional input to the LFC networks from the ventral striatum. These results support the hypotheses that LFC networks interact as a hierarchical system during intentional learning and that signals from the ventral striatum have a driving influence on this system when the internal program for processing the task is updated.

Dynamic Network Mechanisms of Relational Integration

A prominent hypothesis states that specialized neural modules within the human lateral frontopolar cortices (LFPCs) support “relational integration” (RI), the solving of complex problems using inter-related rules. However, it has been proposed that LFPC activity during RI could reflect the recruitment of additional “domain-general” resources when processing more difficult problems in general as opposed to RI specifi- cally. Moreover, theoretical research with computational models has demonstrated that RI may be supported by dynamic processes that occur throughout distributed networks of brain regions as opposed to within a discrete computational module. Here, we present fMRI findings from a novel deductive reasoning paradigm that controls for general difficulty while manipulating RI demands. In accordance with the domain- general perspective, we observe an increase in frontoparietal activation during challenging problems in general as opposed to RI specifically. Nonetheless, when examining frontoparietal activity using analyses of phase synchrony and psychophysiological interactions, we observe increased network connectivity during RI alone. Moreover, dynamic causal modeling with Bayesian model selection identifies the LFPC as the effective connectivity source. Based on these results, we propose that during RI an increase in network connectivity and a decrease in network metastability allows rules that are coded throughout working memory systems to be dynamically bound. This change in connectivity state is top-down propagated via a hierarchical system of domain-general networks with the LFPC at the apex. In this manner, the functional network perspective reconciles key propositions of the globalist, modular, and computational accounts of RI within a single unified framework.

Molecular mechanisms controlling synaptic recruitment of GluA4 subunit-containing AMPAreceptors

Synaptic recruitment of AMPA receptors (AMPARs) represents a key postsynaptic mechanism driving functional development and maturation of glutamatergic synapses. At immature hippocampal synapses, PKA-driven synaptic insertion of GluA4 is the predominant mechanism for synaptic reinforcement. However, the physiological significance and molecular determinants of this developmentally restricted form of plasticity are not known. Here we show that PKA activation leads to insertion of GluA4 to synaptic sites with initially weak or silent AMPAR-mediated transmission. This effect depends on a novel mechanism involving the extreme C-terminal end of GluA4, which interacts with the membrane proximal region of the C-terminal domain to control GluA4 trafficking. In the absence of GluA4, strengthening of AMPAR-mediated transmission during postnatal development was significantly delayed. These data suggest that the GluA4-mediated activation of silent synapses is a critical mechanism facilitating the functional maturation of glutamatergic circuitry during the critical period of experience-dependent fine-tuning.

Contribution of direct electron transfer mechanisms to overall electron transfer in microbial fuel cells utilising Shewanella oneidensis as biocatalyst

Objectives To investigate the contribution of direct electron transfer mechanisms to electricity production in microbial fuel cells by physically retaining Shewanella oneidensis cells close to or away from the anode electrode. Results A maximum power output of 114 ± 6 mWm−2 was obtained when cells were retained close to the anode using a dialysis membrane. This was 3.5 times more than when the cells were separated away from the anode. Without the membrane the maximum power output was 129 ± 6 mWm−2. The direct mechanisms of electron transfer contributed significantly to overall electron transfer from S. oneidensis to electrodes, a result that was corroborated by another experiment where S. oneidensis cells were entrapped in alginate gels. Conclusion S. oneidensis transfers electrons primarily by direct electron transfer as opposed to mediated electron transfer.