Browsing by Subject "Transcranial magnetic stimulation"

Making decisions is fundamental to everything we do, yet it can be impaired in various disorders and conditions. While research into the neural basis of decision-making has flourished in recent years, many questions remain about how decisions are instantiated in the brain. Here we explored how primates make abstract decisions and decisions in social contexts, as well as one way to non-invasively modulate the brain circuits underlying decision-making. We used rhesus macaques as our model organism. First we probed numerical decision-making, a form of abstract decision-making. We demonstrated that monkeys are able to compare discrete ratios, choosing an array with a greater ratio of positive to negative stimuli, even when this array does not have a greater absolute number of positive stimuli. Monkeys’ performance in this task adhered to Weber’s law, indicating that monkeys—like humans—treat proportions as analog magnitudes. Next we showed that monkeys’ ordinal decisions are influenced by spatial associations; when trained to select the fourth stimulus from the bottom in a vertical array, they subsequently selected the fourth stimulus from the left—and not from the right—in a horizontal array. In other words, they begin enumerating from one side of space and not the other, mirroring the human tendency to associate numbers with space. These and other studies confirmed that monkeys’ numerical decision-making follows similar patterns to that of humans, making them a good model for investigations of the neurobiological basis of numerical decision-making.

We sought to develop a system for exploring the neuronal basis of the cognitive and behavioral effects observed following transcranial magnetic stimulation, a relatively new, non-invasive method of brain stimulation that may be used to treat clinical disorders. We completed a set of pilot studies applying offline low-frequency repetitive transcranial magnetic stimulation to the macaque posterior parietal cortex, which has been implicated in numerical processing, while subjects performed a numerical comparison and control color comparison task, and while electrophysiological activity was recorded from the stimulated region of cortex. We found tentative evidence in one paradigm that stimulation did selectively impair performance in the number task, causally implicating the posterior parietal cortex in numerical decisions. In another paradigm, however, we manipulated the subject’s reaching behavior but not her number or color comparison performance. We also found that stimulation produced variable changes in neuronal firing and local field potentials. Together these findings lay the groundwork for detailed investigations into how different parameters of transcranial magnetic stimulation can interact with cortical architecture to produce various cognitive and behavioral changes.

Finally, we explored how monkeys decide how to behave in competitive social interactions. In a zero-sum computer game in which two monkeys played as a shooter or a goalie during a hockey-like “penalty shot” scenario, we found that shooters developed complex movement trajectories so as to conceal their intentions from the goalies. Additionally, we found that neurons in the dorsolateral and dorsomedial prefrontal cortex played a role in generating this “deceptive” behavior. We conclude that these regions of prefrontal cortex form part of a circuit that guides decisions to make an individual less predictable to an opponent.

Transcranial electric stimulation (tES) and magnetic stimulation (TMS) can noninvasively modulate brain activity in humans, offering broad research and therapeutic applications. However, improving the efficacy and selectivity of these techniques is challenging without a mechanistic understanding of how the stimulation parameters determine the neural response and how these parameters can be manipulated to activate specific neural circuits. This dissertation presents multiscale computational models that predict the neural response to TMS and tES at the single-cell and population levels for analysis and rational design of transcranial brain stimulation.We adapted biophysically-realistic models of cortical neurons from the Blue Brain network to the properties of mature rat and human neurons and characterized the direct response to extracellular stimulation with both subthreshold and suprathreshold electric field (E-field) stimulation modalities. These models included 3D reconstructed axonal and dendritic arbors as well as multiple excitatory and inhibitory cell types with validated electrophysiological behavior. Axon terminals were the lowest threshold elements for stimulation, and their dependence on threshold and polarization was determined by cell-type specific morphological features, such as myelination, diameter, and branching. However, we found for TMS pulse waveforms specifically, activation thresholds were higher than expected from in vivo applications. We improved the fidelity of the axon models further using a feature-based optimization algorithm, but these modifications did not produce models with significantly lower thresholds, suggesting other factors may allow for suprathreshold activation at the E-field intensities induced experimentally. The neuron models were then embedded in anatomically-realistic volume conductor head models of the E-field in humans derived from magnetic resonance imaging (MRI) data to simulate the direct neural response to TMS and tDCS. The models reproduced relative trends in motor thresholds as well as the experimentally-measured strength–duration time constant. TMS activated with lowest intensity intracortical axon terminals in the superficial gyral crown and lip region, proportional to the E-field magnitude. Thresholds were lowest for the L5 pyramidal cells (PCs), with activation of the L2/3 PCs and large basket cells at most intensities. Reversing the pulse direction revealed waveform-dependent spatial shifts in the activated neural population that may explain experimentally observed differences in the latencies and thresholds of muscle responses to TMS of motor cortex. We also quantified the subthreshold polarization generated by conventional tDCS with large rectangular pad electrodes and 4×1 high definition (HD) tDCS electrodes targeting the motor hand knob. Axonal and dendritic terminal polarization was higher than somatic polarization in all cell types, and polarization trends between cell types varied by subcellular compartment. While the HD tDCS montage produced a significantly more focal E-field within the brain, both montages generated broad regions of depolarization and hyperpolarization beneath the electrodes. These simulations demonstrated the importance of coupling the E-field to neuron models incorporating non-linear membrane dynamics and realistic morphologies for predicting the neural response to TMS and tES. Indeed, extrapolating the neural response (polarization or threshold) from the uniform E-field or macroscopic E-field components often led to erroneous predictions. Due to the high computational cost of these biophysically-realistic models, we also developed rapid estimators of the neural response using a 3D convolutional neural network. This approach allowed for reproducing the threshold distributions of the realistic model neurons with several orders of magnitude shorter run times than using the E-field distribution alone. In sum, this work provides both computational tools and mechanistic insights to improve the use and development of transcranial magnetic and electrical stimulation technologies.

Transcranial magnetic stimulation, or TMS, is a non-invasive stimulation method which induces an electric field in the brain. For the past two decades it has been used extensively in clinical and research settings for basic research and treatment studies of neurological disorders such as depression. Despite its widespread use and established safety, the mechanism of effect for the stimulation is still poorly understood. The goal of this project is to study the effect of single pulse TMS on single neurons in awake rhesus macaques. By using the modified electronics developed by Mueller et al. (2014), we were able to minimize the duration of the stimulus artifact in the recordings down to a few milliseconds, allowing us to capture and characterize the neural activity in the frontal eye field (FEF) and primary motor cortex (M1) immediately following a TMS pulse. We found that the intracranial electric field induced by TMS has a variety of effects on individual neurons but a distinct pattern of effect on the population activity: a short-latency excitation (<20ms latency) followed by a longer-lasting inhibition (for ~100 ms). These effects were absent in Sham TMS treatments. Our single pulse TMS protocol caused no long term effects on neural activity, but repetitive TMS (rTMS) protocols of 1 and 5 Hz changed spontaneous firing rates. The outcome of this work is to demonstrate empirically how TMS affects neurons in the primate brain.

All of us are taxed with juggling our inner mental lives with immediate external task demands. For many years, the temporary maintenance of internal information was considered to be handled by a dedicated working memory (WM) system. It has recently become increasingly clear, however, that such short-term internal activation interacts with attention focused on external stimuli. It is unclear, however, exactly why these two interact, at what level of processing, and to what degree. Because our internal maintenance and external attention processes co-occur with one another, the manner of their interaction has vast implications for functioning in daily life. The work described here has employed original experimental paradigms combining WM and attention task elements, functional magnetic resonance imaging (fMRI) to illuminate the associated neural processes, and transcranial magnetic stimulation (TMS) to clarify the causal substrates of attentional brain function. These studies have examined a mechanism that might explain why (and when) the content of WM can involuntarily capture visual attention. They have, furthermore, tested whether fundamental attentional selection processes operate within WM, and whether they are reciprocal with attention. Finally, they have illuminated the neural consequences of competing attentional demands. The findings indicate that WM shares representations, operating principles, and cognitive resources with externally-oriented attention.