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Songbirds are outstanding models of motor sequence generation, but commonly-studied species do not share the long-range correlations of human behavior – skills like speech where sequences of actions follow syntactic rules in which transitions between elements depend on the identity and order of past actions. To support long-range correlations, the ‘many-to-one’ hypothesis suggests that redundant premotor neural activity patterns, called ‘hidden states’, carry short-term memory of preceding actions.

To test this hypothesis, we recorded from the premotor nucleus HVC in a rarely-studied species - canaries - whose complex sequences of song syllables follow long-range syntax rules, spanning several seconds.

In song sequences spanning up to four seconds, we found neurons whose activity depends on the identity of previous, or upcoming transitions - reflecting hidden states encoding song context beyond ongoing behavior and demonstrating a deep many-to-one mapping between HVC states and song syllables. We find that context-dependent activity correlates more often with the song’s past than its future, occurs selectively in history-dependent transitions, and also encodes timing information. Together, these findings reveal a novel pattern of neural dynamics that can support structured, context-dependent song transitions and validate predictions of syntax generation by hidden neural states in a complex singer.

Several natural processes are mediated by the interactions between organic and inorganic materials. The immune response towards an implant inserted into the body is mediated by proteins. Composite materials are formed by the interactions of organic materials (usually proteins) and minerals. Biofouling, the process in which organisms attached to surfaces, is also mediated by organic molecules. Understanding the nature of interactions between organic and inorganic materials will bring to the development of improved implants, new composites and antifouling materials.
This lecture will present single-molecule force spectroscopy measurements of the interactions between individual biomolecules (either amino acid residues or short peptides) and inorganic surfaces in aqueous solution. Using this method, we were able to measure low adhesion forces and could clearly determine the strength of interactions between individual amino acid residues and inorganic substrates. Our results with peptides also shed light on the factors that control the interactions at the organic-inorganic interface.
Based on our knowledge from single molecule experiments, we designed a short peptide (tripeptide) that can spontaneously form a coating that resists biofilm formation. Our results clearly demonstrate the formation of a coating on various surfaces (glass, titanium, silicon oxide, metals and polymers). This coating prevents the first step of antifouling, which involves the adsorption of bioorganic molecules to the substrate. In addition, it significantly reduces the attachment of various organisms such as bacteria and fungi to surfaces. Another variation of this peptide can encourage the adhesion of mammalian cells while preventing biofilm formation.

The nervous system of sexually reproducing species is built to accommodate their sex-specific needs and thus contains sexually dimorphic properties. Males and females respond to environmental sensory cues and transform the input into sexually dimorphic traits. New findings reveal a significant difference in the way the two sexes in the nematode C. elegans respond to aversive stimuli. Further analysis of the function of the circuit for aversive behaviors unveiled how stimuli elicit non-dimorphic sensory neuronal activity, proceeded by dimorphic postsynaptic interneuron activity, generating the sexually dimorphic behavior. Here, we propose to uncover how genetic sex defines the properties of the sex-shared circuit for aversive behaviors. We will explore the circuit at the behavioral, connectome and genetic levels. Using calcium imaging, optogenetics, synaptic trans-labeling, transcriptome profiling and a candidate gene approach we will map the functional connections and define the dimorphic responses of all the cells in the avoidance circuit in both sexes. Since in vertebrates and invertebrates, males and females share most of the nervous system, studies of the development of dimorphic aspects of the shared nervous system are crucial for understanding the effects of sex on brain and behavior and specifically, how do changes in connectivity generate dimorphic behaviors, and how both are modulated by the genetic sex.

In a couple of years from now, we will finish kernel programming for Spinach – a spin dynamics simulation library that supports all types of magnetic resonance spectroscopy, from Gd3+ DEER, through DNP and NMR, and all the way to singlet state diffusion MRI, including chemical kinetics, optimal control, and advanced relaxation theories. This level of generality hinges on:

1. The ability to treat classical degrees of freedom (diffusion, hydrodynamics, radiofrequency and microwave phases, stochastic tumbling, etc.) at the same conceptual level as spin degrees of freedom – the corresponding classical equations of motion must be integrated into the density matrix formalism.

2. The ability to survive enormous Kronecker products. A well digitised medical phantom would have at least a hundred points in each of the three directions, meaning a dimension of at least 1003 = 106 for the spatial dynamics generator matrices. At the same time, a typical radical contains upwards of ten coupled spins, meaning a Liouville space dimension of at least 410. Direct products of spin and spatial dynamics generators would then have the dimension in excess of 1012 even before chemical kinetics is considered.

3. Code parallelisation over cluster architectures, including the possibility of using a GPU on each node of the cluster. The principal problem is parallelisation mode switching between powder averages, indirect dimensions of pulse sequences, frequency points of frequency domain simulations, etc. – each simulation type would in general require a different mode of parallelisation and GPU utilisation.

This report is about solving all of this, and on where the dark art of simulating a time-domain magnetic resonance experiment stands at the moment. Two recent innovations are the abandonment of Liouville equation in favour of Fokker-Planck equation as the core formalism, and the use of tensor structured objects that never open Kronecker products. A separate story is recent GPUs: NVidia Tesla V100 performs ~1013 double-precision multiplications per second – an astounding amount of computing power that is surprisingly easy to use.

The preservation of the organic matter (OM) occurs as a result of post-depositional abiotic sulfurization, condensation and polymerization processes that convert the OM into stable macromolecular material termed kerogen. Different sulfurization processes, pathways and rates affect the 34S values of organic and inorganic S compounds. These sulfurization processes are affected by the redox conditions and paleo-environmental conditions (e.g. organic matter and Fe availability). Therefore, studying the organic and inorganic S distribution and their associated 34S values could be useful for understanding the paleo-environmental history associated with the deposition of ancient organic rich sediments. Until recently, only bulk phases of S could be measured for their 34S values, usually excluding organic S. A new method was developed that allows for S isotope analysis of specific organic S compounds (OSCs) at the sub- nanogram level. In my talk I will give an overview about the utility of compound specific S isotope analysis (CSSIA) for the study of different geochemical environments (e.g., immature organic rich sediments). Applying CSSIA to immature organic rich sediments from the Monterey and Ghareb formations I will show the combination of biomarkers and their S isotope composition in a single analysis. This provides a more detailed and in-depth understanding of the S and C cycles than bulk measurements of organic and inorganic S species alone.