Decoding motor intentions from human brain activity

“You read my mind.” Although this simple everyday expression implies ‘knowledge or understanding’ of another’s thinking, true ‘mind-reading’ capabilities implicitly seem constrained to the domains of Hollywood and science-fiction. In the field of sensorimotor neuroscience, however, significant progress in this area has come from mapping characteristic changes in brain activity that occur prior to an action being initiated. For instance, invasive neural recordings in non-human primates have significantly increased our understanding of how highly cognitive and abstract processes like intentions and decisions are represented in the brain by showing that it is possible to decode or ‘predict’ upcoming sensorimotor behaviors (e.g., movements of the arm/eyes) based on preceding changes in the neuronal output of parieto-frontal cortex, a network of areas critical for motor planning. In the human brain, however, a successful counterpart for this predictive ability and a similar detailed understanding of intention-related signals in parieto-frontal cortex have remained largely unattainable due to the limitations of non-invasive brain mapping techniques like functional magnetic resonance imaging (fMRI). Knowing how and where in the human brain intentions or plans for action are coded is not only important for understanding the neuroanatomical organization and cortical mechanisms that govern goal-directed behaviours like reaching, grasping and looking – movements critical to our interactions with the world – but also for understanding homologies between human and non-human primate brain areas, allowing the transfer of neural findings between species. In the current thesis, I employed multi-voxel pattern analysis (MVPA), a new fMRI technique that has made it possible to examine the coding of neural information at a more fine-grained level than that previously available. I used fMRI MVPA to examine how and where movement intentions are coded in human parieto-frontal cortex and specifically asked the question: What types of predictive information about a subject\u27s upcoming movement can be decoded from preceding changes in neural activity? Project 1 first used fMRI MVPA to determine, largely as a proof-of-concept, whether or not specific object-directed hand actions (grasps and reaches) could be predicted from intention-related brain activity patterns. Next, Project 2 examined whether effector-specific (arm vs. eye) movement plans along with their intended directions (left vs. right) could also be decoded prior to movement. Lastly, Project 3 examined exactly where in the human brain higher-level movement goals were represented independently from how those goals were to be implemented. To this aim, Project 3 had subjects either grasp or reach toward an object (two different motor goals) using either their hand or a novel tool (with kinematics opposite to those of the hand). In this way, the goal of the action (grasping vs. reaching) could be maintained across actions, but the way in which those actions were kinematically achieved changed in accordance with the effector (hand or tool). All three projects employed a similar event-related delayed-movement fMRI paradigm that separated in time planning and execution neural responses, allowing us to isolate the preparatory patterns of brain activity that form prior to movement. Project 1 found that the plan-related activity patterns in several parieto-frontal brain regions were predictive of different upcoming hand movements (grasps vs. reaches). Moreover, we found that several parieto-frontal brain regions, similar to that only previously demonstrated in non-human primates, could actually be characterized according to the types of movements they can decode. Project 2 found a variety of functional subdivisions: some parieto-frontal areas discriminated movement plans for the different reach directions, some for the different eye movement directions, and a few areas accurately predicted upcoming directional movements for both the hand and eye. This latter finding demonstrates -- similar to that shown previously in non-human primates -- that some brain areas code for the end motor goal (i.e., target location) independent of effector used. Project 3 identified regions that decoded upcoming hand actions only, upcoming tool actions only, and rather interestingly, areas that predicted actions with both effectors (hand and tool). Notably, some of these latter areas were found to represent the higher-level goals of the movement (grasping vs. reaching) instead of the specific lower-level kinematics (hand vs. tool) necessary to implement those goals. Taken together, these findings offer substantial new insights into the types of intention-related signals contained in human brain activity patterns and specify a hierarchical neural architecture spanning parieto-frontal cortex that guides the construction of complex object-directed behaviors

A Computational Study of Cation−π Interactions vs Salt Bridges in Aqueous Media: Implications for Protein Engineering

A direct comparison of the energetic significance of a representative salt bridge vs a representative cation−π interaction in aqueous media and in a range of organic solvents is presented using ab initio electronic structures and the SM5.42R/HF solvation model of Cramer and Truhlar. The cation−π interaction shows a well depth of 5.5 kcal/mol in water, significantly larger than the 2.2 kcal/mol seen for the salt bridge. Consistent with this idea, a survey of the Protein Data Bank reveals that energetically significant cation−π interactions are rarely completely buried within proteins, but prefer to be exposed to solvent. These results suggest that engineering surface-exposed cation−π interactions could be a novel way to enhance protein stability

From ab initio quantum mechanics to molecular neurobiology: A cation-pi binding site in the nicotinic receptor

The nicotinic acetylcholine receptor is the prototype ligand-gated ion channel. A number of aromatic amino acids have been identified as contributing to the agonist binding site, suggesting that cation-pi interactions may be involved in binding the quaternary ammonium group of the agonist, acetylcholine. Here we show a compelling correlation between: (i) ab initio quantum mechanical predictions of cation-pi binding abilities and (ii) EC50 values for acetylcholine at the receptor for a series of tryptophan derivatives that were incorporated into the receptor by using the in vivo nonsense-suppression method for unnatural amino acid incorporation. Such a correlation is seen at one, and only one, of the aromatic residues-tryptophan-149 of the alpha subunit. This finding indicates that, on binding, the cationic, quaternary ammonium group of acetylcholine makes van der Waals contact with the indole side chain of alpha tryptophan-149, providing the most precise structural information to date on this receptor. Consistent with this model, a tethered quaternary ammonium group emanating from position alpha 149 produces a constitutively active receptor

First-order optimization on stratified sets

We consider the problem of minimizing a differentiable function with locally Lipschitz continuous gradient on a stratified set and present a first-order algorithm designed to find a stationary point of that problem. Our assumptions on the stratified set are satisfied notably by the determinantal variety (i.e., matrices of bounded rank), its intersection with the cone of positive-semidefinite matrices, and the set of nonnegative sparse vectors. The iteration map of the proposed algorithm applies a step of projected-projected gradient descent with backtracking line search, as proposed by Schneider and Uschmajew (2015), to its input but also to a projection of the input onto each of the lower strata to which it is considered close, and outputs a point among those thereby produced that maximally reduces the cost function. Under our assumptions on the stratified set, we prove that this algorithm produces a sequence whose accumulation points are stationary, and therefore does not follow the so-called apocalypses described by Levin, Kileel, and Boumal (2022). We illustrate the apocalypse-free property of our method through a numerical experiment on the determinantal variety

Site-specific incorporation of biotinylated amino acids to identify surface-exposed residues in integral membrane proteins

AbstractBackground: A key structural issue for all integral membrane proteins is the exposure of individual residues to the intracellular or extracellular media. This issue involves the basic transmembrane topology as well as more subtle variations in surface accessibility. Direct methods to evaluate the degree of exposure for residues in functional proteins expressed in living cells would be highly valuable. We sought to develop a new experimental method to determine highly surface-exposed residues, and thus transmembrane topology, of membrane proteins expressed in Xenopus oocytes.Results: We have used the in vivo nonsense suppression technique to incorporate biotinylated unnatural amino acids into functional ion channels expressed in Xenopus oocytes. Binding of 125I-streptavidin to biotinylated receptors was used to determine the surface exposure of individual amino acids. In particular, we studied the main immunogenic region of the nicotinic acetylcholine receptor. The biotin-containing amino acid biocytin was efficiently incorporated into five sites in the main immunogenic region and extracellular streptavidin bound to one residue in particular, α70. The position of α70 as highly exposed on the receptor surface was thus established.Conclusions: The in vivo nonsense suppression technique has been extended to provide the first in a potential series of methods to identify exposed residues and to assess their relative exposure in functional proteins expressed in Xenopus oocytes

Planning Ahead: Object-Directed Sequential Actions Decoded from Human Frontoparietal and Occipitotemporal Networks.

Object-manipulation tasks (e.g., drinking from a cup) typically involve sequencing together a series of distinct motor acts (e.g., reaching toward, grasping, lifting, and transporting the cup) in order to accomplish some overarching goal (e.g., quenching thirst). Although several studies in humans have investigated the neural mechanisms supporting the planning of visually guided movements directed toward objects (such as reaching or pointing), only a handful have examined how manipulatory sequences of actions-those that occur after an object has been grasped-are planned and represented in the brain. Here, using event-related functional MRI and pattern decoding methods, we investigated the neural basis of real-object manipulation using a delayed-movement task in which participants first prepared and then executed different object-directed action sequences that varied either in their complexity or final spatial goals. Consistent with previous reports of preparatory brain activity in non-human primates, we found that activity patterns in several frontoparietal areas reliably predicted entire action sequences in advance of movement. Notably, we found that similar sequence-related information could also be decoded from pre-movement signals in object- and body-selective occipitotemporal cortex (OTC). These findings suggest that both frontoparietal and occipitotemporal circuits are engaged in transforming object-related information into complex, goal-directed movements

Motor, not visual, encoding of potential reach targets

SummaryWe often encounter situations in which there are multiple potential targets for action, as when, for example, we hear the request “could you pass the …” at the dinner table. It has recently been shown that, in such situations, activity in sensorimotor brain areas represents competing reach targets in parallel prior to deciding between, and then reaching towards, one of these targets [1]. One intriguing possibility, consistent with the influential notion of action ‘affordances’ [2], is that this activity reflects movement plans towards each potential target [3]. However, an equally plausible explanation is that this activity reflects an encoding of the visual properties of the potential targets (for example, their locations or directions), prior to any target being selected and the associated movement plan being formed. Notably, previous work showing spatial averaging behaviour during reaching, in which initial movements are biased towards the midpoint of the spatial distribution of potential targets [4–6], remains equally equivocal concerning the motor versus visual encoding of reach targets. Here, using a rapid reaching task that disentangles these two competing accounts, we show that reach averaging behaviour reflects the parallel encoding of multiple competing motor plans. This provides direct evidence for theories proposing that the brain prepares multiple available movements before selecting between them [3]

Neural representation of geometry and surface properties in object and scene perception

Multiple cortical regions are crucial for perceiving the visual world, yet the processes shaping representations in these regions are unclear. To address this issue, we must elucidate how perceptual features shape representations of the environment. Here, we explore how the weighting of different visual features affects neural representations of objects and scenes, focusing on the scene-selective parahippocampal place area (PPA), but additionally including the retrosplenial complex (RSC), occipital place area (OPA), lateral occipital (LO) area, fusiform face area (FFA) and occipital face area (OFA). Across three experiments, we examined functional magnetic resonance imaging (fMRI) activity while human observers viewed scenes and objects that varied in geometry (shape/layout) and surface properties (texture/material). Interestingly, we found equal sensitivity in the PPA for these properties within a scene, revealing that spatial-selectivity alone does not drive activation within this cortical region. We also observed sensitivity to object texture in PPA, but not to the same degree as scene texture, and representations in PPA varied when objects were placed within scenes. We conclude that PPA may process surface properties in a domain-specific manner, and that the processing of scene texture and geometry is equally-weighted in PPA and may be mediated by similar underlying neuronal mechanisms

Interpolatory methods for H∞\mathcal{H}_\infty model reduction of multi-input/multi-output systems

We develop here a computationally effective approach for producing high-quality $\mathcal{H}_\infty$-approximations to large scale linear dynamical systems having multiple inputs and multiple outputs (MIMO). We extend an approach for $\mathcal{H}_\infty$ model reduction introduced by Flagg, Beattie, and Gugercin for the single-input/single-output (SISO) setting, which combined ideas originating in interpolatory $\mathcal{H}_2$-optimal model reduction with complex Chebyshev approximation. Retaining this framework, our approach to the MIMO problem has its principal computational cost dominated by (sparse) linear solves, and so it can remain an effective strategy in many large-scale settings. We are able to avoid computationally demanding $\mathcal{H}_\infty$ norm calculations that are normally required to monitor progress within each optimization cycle through the use of "data-driven" rational approximations that are built upon previously computed function samples. Numerical examples are included that illustrate our approach. We produce high fidelity reduced models having consistently better $\mathcal{H}_\infty$ performance than models produced via balanced truncation; these models often are as good as (and occasionally better than) models produced using optimal Hankel norm approximation as well. In all cases considered, the method described here produces reduced models at far lower cost than is possible with either balanced truncation or optimal Hankel norm approximation