Shape-shifting structured lattices via multimaterial 4D printing

October 2, 2019

Boley JW, van Rees WM, Lissandrello C, Horenstein MN, Truby RL, Kotikian A, Lewis JA, Mahadevan L

Shape-morphing structured materials have the ability to transform a range of applications. However, their design and fabrication remain challenging due to the difficulty of controlling the underlying metric tensor in space and time. Here, we exploit a combination of multiple materials, geometry, and 4-dimensional (4D) printing to create structured heterogeneous lattices that overcome this problem. Our printable inks are composed of elastomeric matrices with tunable cross-link density and anisotropic filler that enable precise control of their elastic modulus (E) and coefficient of thermal expansion [Formula: see text] The inks are printed in the form of lattices with curved bilayer ribs whose geometry is individually programmed to achieve local control over the metric tensor. For independent control of extrinsic curvature, we created multiplexed bilayer ribs composed of 4 materials, which enables us to encode a wide range of 3-dimensional (3D) shape changes in response to temperature. As exemplars, we designed and printed planar lattices that morph into frequency-shifting antennae and a human face, demonstrating functionality and geometric complexity, respectively. Our inverse geometric design and multimaterial 4D printing method can be readily extended to other stimuli-responsive materials and different 2-dimensional (2D) and 3D cell designs to create scalable, reversible, shape-shifting structures with unprecedented complexity.

Convergent Temperature Representations in Artificial and Biological Neural Networks

September 25, 2019

Haesemeyer M, Schier AF, Engert F.

Discoveries in biological neural networks (BNNs) shaped artificial neural networks (ANNs) and computational parallels between ANNs and BNNs have recently been discovered. However, it is unclear to what extent discoveries in ANNs can give insight into BNN function. Here, we designed and trained an ANN to perform heat gradient navigation and found striking similarities in computation and heat representation to a known zebrafish BNN. This included shared ON- and OFF-type representations of absolute temperature and rates of change. Importantly, ANN function critically relied on zebrafish-like units. We furthermore used the accessibility of the ANN to discover a new temperature-responsive cell type in the zebrafish cerebellum. Finally, constraining the ANN by the C. elegans motor repertoire retuned sensory representations indicating that our approach generalizes. Together, these results emphasize convergence of ANNs and BNNs on stereotypical representations and that ANNs form a powerful tool to understand their biological counterparts.


A nanoelectrode array for obtaining intracellular recordings from thousands of connected neurons

September 23, 2019

Abbott J, Ye T, Krenek K, Gertner RS, Ban S, Kim Y, Qin L, Wu W, Park H, Ham D.

Current electrophysiological or optical techniques cannot reliably perform simultaneous intracellular recordings from more than a few tens of neurons. Here we report a nanoelectrode array that can simultaneously obtain intracellular recordings from thousands of connected mammalian neurons in vitro. The array consists of 4,096 platinum-black electrodes with nanoscale roughness fabricated on top of a silicon chip that monolithically integrates 4,096 microscale amplifiers, configurable into pseudocurrent-clamp mode (for concurrent current injection and voltage recording) or into pseudovoltage-clamp mode (for concurrent voltage application and current recording). We used the array in pseudovoltage-clamp mode to measure the effects of drugs on ion-channel currents. In pseudocurrent-clamp mode, the array intracellularly recorded action potentials and postsynaptic potentials from thousands of neurons. In addition, we mapped over 300 excitatory and inhibitory synaptic connections from more than 1,700 neurons that were intracellularly recorded for 19 min. This high-throughput intracellular-recording technology could benefit functional connectome mapping, electrophysiological screening and other functional interrogations of neuronal networks.

Dissociating effects of error size, training duration, and amount of adaptation on the ability to retain motor memories

September 4, 2019

Alhussein L, Hosseini EA, Nguyen KP, Smith MA, Joiner WM

Extensive computational and neurobiological work has focused on how the training schedule, i.e. the duration and rate at which an environmental disturbance is presented, shapes the formation of motor memories. If long-lasting benefits are to be derived from motor training, however, retention of the performance improvements gained during practice is essential. Thus, a better understanding of mechanisms that promote retention could lead to the design of more effective training procedures. The few studies that have investigated how retention depends on the training schedule have suggested that the gradual exposure of a perturbation leads to improved retention of motor memory compared to an abrupt exposure. However, several of these previous studies showed small effects, and while some controlled the training duration and others the level of learning, none have controlled both. Here we disambiguated both of these effects from exposure rate by systematically varying the duration of training, the type of trained dynamics, and exposure rate for these dynamics in human force-field adaptation. After controlling for both training duration and the amount of learning, we found essentially identical retention when comparing gradual and abrupt training for two different types of force-field dynamics. By contrast, we found that retention was markedly higher for long-duration compared to short-duration training for both types of dynamics. These results demonstrate that the duration of training has a far greater effect on the retention of motor memory than the exposure rate during training. We show that a multi-rate learning model provides a computational mechanism for these findings.

J Neurophysiol.

Precision electronic medicine in the brain

September 2, 2019

Patel SR, Lieber CM

Periodically throughout history developments from adjacent fields of science and technology reach a tipping point where together they produce unparalleled advances, such as the Allen Brain Atlas and the Human Genome Project. Today, research focused at the interface between the nervous system and electronics is not only leading to advances in fundamental neuroscience, but also unlocking the potential of implants capable of cellular-level therapeutic targeting. Ultimately, these personalized electronic therapies will provide new treatment modalities for neurodegenerative and neuropsychiatric illness; powerful control of prosthetics for restorative function in degenerative diseases, trauma and amputation; and even augmentation of human cognition. Overall, we believe that emerging advances in tissue-like electronics will enable minimally invasive devices capable of establishing a stable long-term cellular neural interface and providing long-term treatment for chronic neurological conditions.

Nat Biotechnol.