Extracting Kinematic Parameters for Monkey Bipedal Walking from Cortical Neuronal Ensemble Activity

The ability to walk may be critically impacted as the result of neurological injury or disease. While recent advances in brain–machine interfaces (BMIs) have demonstrated the feasibility of upper-limb neuroprostheses, BMIs have not been evaluated as a means to restore walking. Here, we demonstrate that chronic recordings from ensembles of cortical neurons can be used to predict the kinematics of bipedal walking in rhesus macaques – both offline and in real time. Linear decoders extracted 3D coordinates of leg joints and leg muscle electromyograms from the activity of hundreds of cortical neurons. As more complex patterns of walking were produced by varying the gait speed and direction, larger neuronal populations were needed to accurately extract walking patterns. Extraction was further improved using a switching decoder which designated a submodel for each walking paradigm. We propose that BMIs may one day allow severely paralyzed patients to walk again

Rosetta Brains: A Strategy for Molecularly-Annotated Connectomics

We propose a neural connectomics strategy called Fluorescent In-Situ Sequencing of Barcoded Individual Neuronal Connections (FISSEQ-BOINC), leveraging fluorescent in situ nucleic acid sequencing in fixed tissue (FISSEQ). FISSEQ-BOINC exhibits different properties from BOINC, which relies on bulk nucleic acid sequencing. FISSEQ-BOINC could become a scalable approach for mapping whole-mammalian-brain connectomes with rich molecular annotations

High-Throughput Mapping of Single-Neuron Projections by Sequencing of Barcoded RNA

Summary Neurons transmit information to distant brain regions via long-range axonal projections. In the mouse, area-to-area connections have only been systematically mapped using bulk labeling techniques, which obscure the diverse projections of intermingled single neurons. Here we describe MAPseq (Multiplexed Analysis of Projections by Sequencing), a technique that can map the projections of thousands or even millions of single neurons by labeling large sets of neurons with random RNA sequences (“barcodes”). Axons are filled with barcode mRNA, each putative projection area is dissected, and the barcode mRNA is extracted and sequenced. Applying MAPseq to the locus coeruleus (LC), we find that individual LC neurons have preferred cortical targets. By recasting neuroanatomy, which is traditionally viewed as a problem of microscopy, as a problem of sequencing, MAPseq harnesses advances in sequencing technology to permit high-throughput interrogation of brain circuits

Converting connectivity into a sequencing problem can be broken down conceptually into three components.

<p>Each component of BOINC has many possible implementations. (A) First, each neuron must be labeled with a unique sequence of nucleotides—a DNA “barcode”. (B) Second, barcodes from synaptically connected neurons must be associated with one another, so that each neuron can be thought of as a “bag of barcodes”: copies of its own “host” barcode and copies of “invader” barcodes from synaptic partners. (C) Finally, host and invader barcodes must be joined into barcode pairs. These pairs can be subjected to high-throughput sequencing.</p

Joining barcodes with phiC31 integrase.

<p>One strategy for joining barcodes is based on phiC31 integrase <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001411#pbio.1001411-Groth1" target="_blank">[25]</a>. PhiC31 mediates the integration of a 35-nucleotide AttB site with a 35-nucleotide AttP site to form an AttL and an AttR site. Because the AttL and AttR sites are not targets of phiC31, this reaction is irreversible (unlike comparable reactions with cre and flp). Once the barcodes are joined, they can be amplified by PCR (using primers complementary to the arrows) for sequencing.</p

The wiring of neural circuits is highly structured.

<p>(A) Descartes' model of the foot withdrawal reflex. (B) Two similar circuits in which the computation is readily deduced from the wiring. The circuit on the top is directionally selective, whereas the one on the bottom performs a center-surround computation. (C) The costs of DNA sequencing are falling exponentially. From 2001 to 2007, the costs of sequencing dropped exponentially, in pace with Moore's law <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001411#pbio.1001411-Moore1" target="_blank">[18]</a> for computation. Since the introduction of “next generation” sequencing technologies in 2008, the cost of sequencing has fallen more than 10-fold every year, compared with the steady 1.4-fold yearly drop for computing power. Data from <a href="http://www.genome.gov/sequencingcosts/" target="_blank">http://www.genome.gov/sequencingcosts/</a>.</p

Beyond the abstract connectivity matrix.

<p>(A) The connectivity of the circuit obtained through sequencing can be read out by filling in the entries of a (sparse) connectivity matrix based on which host-invader barcode pairs that were found by sequencing to be joined together. (B) The sequencing approach can be extended to recover information about brain region. To associate each barcode with a specific brain region, the brain can be sectioned prior to extracting barcodes. The DNA extracted from each section can be sequenced separately, or DNA from multiple regions can be pooled after adding a DNA tag to each region. The size of the sections determines the spatial resolution to location of each barcode; a resolution of a few hundred microns could be easily achieved and would suffice for many purposes (e.g., to distinguish nearby structures such as auditory and visual cortex). (C) The sequencing approach can be extended to recover information about brain region and cell type. To make inferences about the cell type from each barcode that arose, mRNA transcripts from each cell can be barcoded (e.g., by RNA transsplicing <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001411#pbio.1001411-Puttaraju1" target="_blank">[26]</a>). Thus, if barcode 242 were found tagging both GAD-67 and parvalbumin, neuron 242 would likely be a fast-spiking GABAergic interneuron.</p