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Orienting behaviors provide a continuous stream of information about an organism’s sensory experiences and plans. Thus, to study the links between sensation and action, it is useful to identify the neurons in the brain that control orienting behaviors. Here, we describe descending neurons in the Drosophila brain that predict and influence orientation (heading) during walking. We show that these cells have specialized functions: whereas one cell type predicts sustained low-gain steering, the other predicts transient high-gain steering. These latter cells integrate internally directed steering signals from the head direction system with stimulus-directed steering signals from multimodal sensory pathways. The inputs to these cells are organized to produce ‘see-saw’ steering commands, so that increasing output from one brain hemisphere is accompanied by decreasing output from the other hemisphere. Together, our results show that internal and external drives are integrated to produce descending motor commands with different timescales, for flexible and precise control of an organism’s orientation in space.

An almost sinusoidal, large amplitude ~0.1 Hz oscillation in cortical hemodynamics has been repeatedly observed in species ranging from mice to humans. However, the occurrence of 'slow sinusoidal hemodynamic oscillations' (SSHOs) in human functional magnetic resonance imaging (fMRI) studies is rarely noted or considered. As a result, little investigation into the cause of SSHOs has been undertaken, and their potential to confound fMRI analysis, as well as their possible value as a functional biomarker has been largely overlooked. Here, we report direct observation of large-amplitude, sinusoidal ~0.1 Hz hemodynamic oscillations in the cortex of an awake human undergoing surgical resection of a brain tumor. Intraoperative multispectral optical intrinsic signal imaging (MS-OISI) revealed that SSHOs were spatially localized to distinct regions of the cortex, exhibited wave-like propagation, and involved oscillations in the diameter of specific pial arterioles, indicating that the effect was not the result of systemic blood pressure oscillations. fMRI data collected from the same subject 4 days prior to surgery demonstrates that ~0.1 Hz oscillations in the BOLD signal can be detected around the same region. Intraoperative optical imaging data from a patient undergoing epilepsy surgery, in whom sinusoidal oscillations were not observed, is shown for comparison. This direct observation of the '0.1 Hz wave' in the awake human brain, using both intraoperative imaging and pre-operative fMRI, confirms that SSHOs occur in the human brain, and can be detected by fMRI. We discuss the possible physiological basis of this oscillation and its potential link to brain pathologies, highlighting its relevance to resting-state fMRI and its potential as a novel target for functional diagnosis and delineation of neurological disease.

Orienting behaviors provide a continuous stream of information about an organism’s sensory experiences and plans. Thus, to study the links between sensation and action, it is useful to identify the neurons in the brain that control orienting behaviors. Here, we describe descending neurons in the Drosophila brain that predict and influence orientation (heading) during walking. We show that these cells have specialized functions: whereas one cell type predicts sustained low-gain steering, the other predicts transient high-gain steering. These latter cells integrate internally directed steering signals from the head direction system with stimulus-directed steering signals from multimodal sensory pathways. The inputs to these cells are organized to produce ‘see-saw’ steering commands, so that increasing output from one brain hemisphere is accompanied by decreasing output from the other hemisphere. Together, our results show that internal and external drives are integrated to produce descending motor commands with different timescales, for flexible and precise control of an organism’s orientation in space.

An almost sinusoidal, large amplitude ~0.1Hz oscillation in cortical hemodynamics has been repeatedly observed in species ranging from mice to humans. However, the occurrence of ‘slow sinusoidal hemodynamic oscillations’ (SSHOs) in human functional magnetic resonance imaging (fMRI) studies is rarely noted or considered. As a result, little investigation into the cause of SSHOs has been undertaken, and their potential to confound fMRI analysis, as well as their possible value as a functional biomarker has been largely overlooked. Here, we report direct observation of large-amplitude, sinusoidal ~0.1Hz hemodynamic oscillations in the cortex of an awake human undergoing surgical resection of a brain tumor. Intraoperative multispectral optical intrinsic signal imaging (MS-OISI) revealed that SSHOs were spatially localized to distinct regions of the cortex, exhibited wave-like propagation, and involved oscillations in the diameter of specific pial arterioles, indicating that the effect was not the result of systemic blood pressure oscillations. fMRI data collected from the same subject 4days prior to surgery demonstrates that ~0.1Hz oscillations in the BOLD signal can be detected around the same region. Intraoperative optical imaging data from a patient undergoing epilepsy surgery, in whom sinusoidal oscillations were not observed, is shown for comparison. This direct observation of the ‘0.1Hz wave’ in the awake human brain, using both intraoperative imaging and pre-operative fMRI, confirms that SSHOs occur in the human brain, and can be detected by fMRI. We discuss the possible physiological basis of this oscillation and its potential link to brain pathologies, highlighting its relevance to resting-state fMRI and its potential as a novel target for functional diagnosis and delineation of neurological disease. •Direct observation of ~0.1Hz oscillation in awake human cortex.•Oscillation in frequency range of resting state function connectivity analysis.•Oscillation delineates vascular networks.•~0.1Hz oscillations are also observed in pre-operative fMRI BOLD signal.•Potential novel target for functional diagnosis of neurological disease.

Steering is a fundamental component of orienting behavior. It can be guided by external sensory cues, internal drives, and goal directions stored in working memory. Steering behavior provides an opportunity to study how the brain toggles between these different drives with different goals. It also provides an opportunity to study how the brain combines steering guidance information from multiple sensory modalities with steering guidance information in working memory. How sensory cues and internal cognitive drives are integrated to guide motor commands is a major open problem. In this study we made significant progress toward solving this problem by identifying two types of descending neurons (a1 and a2) that influence steering during walking in Drosophila. Whereas a1 acts in a sustained manner with low gain, and a2 acts transiently with high gain. We showed that a2 responds to spatial guidance cues with different valences from multiple stimulus modalities. These neurons encode the direction of the cue evoked turn, not the side of the body where the cue was delivered. Moreover, we showed that a2 is functionally downstream from the heading direction map in the central complex, and it can participate in steering behavior driven by central complex dynamics. Finally, we suggest future strategies for examining the mechanism of integration between central complex-related inputs and sensory-related inputs onto steering descending neurons.

This paper presents results on a communications-intensive kernel, the three-dimensional fast Fourier transform (3D FFT), running on the 2,048-node Blue Gene®/L (BG/L) prototype. Two implementations of the volumetric FFT algorithm were characterized, one built on the Message Passing Interface library and another built on an active packet Application Program Interface supported by the hardware bring-up environment, the BG/L advanced diagnostics environment. Preliminary performance experiments on the BG/L prototype indicate that both of our implementations scale well up to 1,024 nodes for 3D FFTs of size 128 × 128 × 128. The performance of the volumetric FFT is also compared with that of the Fastest Fourier Transform in the West (FFTW) library. In general, the volumetric FFT outperforms a port of the FFTW Version 2.1.5 library on large-node-count partitions. [PUBLICATION ABSTRACT]

N-body simulations present some of the most interesting challenges in the area of massively parallel computing, especially when the object is to improve the time to solution for a fixed-size problem. The Blue Matter molecular simulation framework was developed specifically to address these challenges, to explore programming models for massively parallel machine architectures in a concrete context, and to support the scientific goals of the IBM Blue Gene® Project. This paper reviews the key issues involved in achieving ultrastrong scaling of methodologically correct biomolecular simulations, particularly the treatment of the long-range electrostatic forces present in simulations of proteins in water and membranes. Blue Matter computes these forces using the particle-particle particle-mesh Ewald (P3ME) method, which breaks the problem up into two pieces, one that requires the use of three-dimensional fast Fourier transforms with global data dependencies and another that involves computing interactions between pairs of particles within a cutoff distance. We summarize our exploration of the parallel decompositions used to compute these finite-ranged interactions, describe some of the implementation details involved in these decompositions, and present the evolution of strong-scaling performance achieved over the course of this exploration, along with evidence for the quality of simulation achieved. [PUBLICATION ABSTRACT]

Animals interact with unfamiliar objects to learn about their properties and guide future behavior, but the underlying neurobiological mechanism is not well understood. Here, we developed a behavioral paradigm in which freely walking Drosophila melanogaster are repeatedly guided to spherical objects using a visual cue. Flies exhibited diverse and structured object interaction motifs, including “ball pulling”, and “ball walking”, that evolved over time. Notably, flies developed a strong preference for immobile over mobile spherical objects, despite their near identical appearance, suggesting they learn about the object’s stability through physical interaction. This preference was impaired by silencing specific hΔ neurons in the fan-shaped body, previously implicated in spatial navigation but not known to contribute to object interactions. Our results show that hΔ neurons also modulate object interaction motifs and fidelity of following visual guidance cues, pointing to a role in balancing goal-directed and exploratory behaviors. These findings establish Drosophila as a model for investigating how internal representations and multimodal feedback contribute to adaptive object interaction.

Engineering small autonomous agents capable of operating in the microscale environment remains a key challenge, with current systems still evolving. Our study explores the fruit fly, Drosophila melanogaster, a classic model system in biology and a species adept at microscale interaction, as a biological platform for micro-robotics. Initially, we focus on remotely directing the walking paths of fruit flies in an experimental arena. We accomplish this through two distinct approaches: harnessing the fruit flies’ opto-motor response and optogenetic modulation of its olfactory system. These techniques facilitate reliable and repeated guidance of flies between arbitrary spatial locations. We guide flies along predetermined trajectories, enabling them to scribe patterns resembling textual characters through their locomotion. We enhance olfactory-guided navigation through additional optogenetic activation of positive valence mushroom body output neurons. We extend this control to collective behaviors in shared spaces and navigation through constrained maze-like environments. We further use our guidance technique to enable flies to carry a load across designated points in space, establishing the upper bound on their weight carrying capabilities. Additionally, we demonstrate that visual guidance can facilitate novel interactions between flies and objects, showing that flies can consistently relocate a small spherical object over significant distances. Beyond expanding tools available for micro-robotics, these novel behavioral contexts can provide insights into the neurological basis of behavior in fruit flies.

Blue Matter is the application framework being developed in conjunction with the scientific portion of the IBM Blue Gene® project. We describe the parallel decomposition currently being used to target the Blue Gene/L machine and discuss the application-based trace tools used to analyze the performance of the application. We also present the results of early performance studies, including a comparison of the performance of the Ewald and the particle-particle particle-mesh (P3ME) methods, compare the measured performance of some key collective operations with the limitations imposed by the hardware, and discuss some future directions for research. [PUBLICATION ABSTRACT]