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Transforming the understanding
and treatment of mental illnesses.

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Danielle Bassett, PhD (University of Pennsylvania)

Title: Network Controllability as a Fundamental Mechanism of Executive Function

Abstract: Cognitive function is driven by dynamic interactions between large-scale neural circuits or networks, enabling behavior. Fundamental principles constraining these dynamic network processes have remained elusive. I will discuss a recent application of network control theory to human neuroimaging data that provides new insights into the structural network mechanisms of human brain function. Using diffusion spectrum imaging data, we build a structural brain network with 234 nodes (brain regions) connected by weighted edges (number of white matter streamlines linking brain regions). We employ a simplified noise-free linear discrete-time and time-invariant network model of neural dynamics in which the state of brain regions depends on the connectivity between them. We interrogate this model to determine the role of brain regions in different control strategies. Our results suggest that densely connected areas, particularly in the default mode system, facilitate the movement of the brain to many easily-reachable states. Weakly connected areas, particularly in cognitive control systems, facilitate the movement of the brain to difficult-to-reach states. Areas located on the boundary between network communities, particularly in attentional control systems, facilitate the integration or segregation of diverse cognitive systems. As a whole, this body of work suggests that structural network differences between the default mode, cognitive control, and attentional control systems dictate their distinct roles in controlling brain network function. More generally, our results support the view that macroscale structural design underlies basic cognitive control processes via the fundamental mechanism of network controllability.

György Buzsáki, MD, PhD (The Neuroscience Institute, New York University)

Title: Synchrony, asynchrony and metachrony: implications for open- and closed-loop interventions

Abstract: Oscillations gained the reputation as an effective mechanism for synchronizing neurons. Indeed, synchrony is an effective way to address downstream targets by members of an assembly. An often-used argument against the utility of oscillations that e.g., in the visual system neurons are most strongly decorrelated (i.e., desynchronized) during focused attention when the network is mostly involved in its key function. I will demonstrate that this is also the case for hippocampal theta oscillations. However, the appropriate descriptor of this state is not desynchrony but metachrony, which is a temporally organized sequence. Theta-gamma phase amplitude coupling allows that multiple cell assemblies are sequentially activated during the entire phase space of the theta cycle. Metachrony is also present is space since cell assemblies are activated sequentially in a traveling wave manner along the long axis of the hippocampus. Such spatio-temporal metachronous organization places challenges for intervention strategies, most of which tend to synchronize neuronal events.

Flavio Frohlich, PhD (University of North Carolina at Chapel Hill)

Title: Targeting Cortical Oscillations: From Computational Models to Clinical Trials

Abstract: Non-invasive brain stimulation has the potential to safely and effectively modulate cortical network dynamics. Recently, targeting of cortical oscillations by brain stimulation with periodic stimulation waveforms, in particular transcranial alternating current stimulation (tACS), has emerged as a particularly appealing approach for understanding the causal role of cortical oscillations in human cognition and behavior. One of the main lessons that the field of non-invasive brain stimulation has learnt over the last few years is that without a mechanistic understanding of how stimulation engages neuronal circuits, little progress can be made towards the rational design of individualized, adaptive stimulation treatments. A key tool to accomplish such a mechanistic understanding is the use of computational models. However, such modeling strategies can only be fully leveraged in tight conjunction with experimental approaches in both humans and animal model studies. Here, we provide an update on our work that vertically integrates computer simulations, in vitro and in vivo animal electrophysiology, and human studies. The aim of this approach is to provide the basis for the development of brain stimulation treatment strategies for disorders associated with specific deficits in cortical oscillations.

Stephanie Jones, PhD (Brown University)

Title: Bridging the gap between MEG/EEG measured rhythms and their underlying cellular and network level generators with biophysically principled computational neural models

Abstract: Low frequency neocortical rhythms are among the most prominent activity measured non-invasively in humans with electro- and magnetoencephalography (EEG/MEG). Their expression and modulation play a key role in perception, cognition and action, and their disruption is a hallmark of many diseases. As such, causal manipulation of these rhythms with techniques such as transcranial direct/alternating electrical current stimulation (tDC/ACS) or magnetic stimulation (TMS) provides a potentially powerful avenue to improve brain function in health and disease. A critical challenge in designing stimulation protocols that optimally manipulate human brain rhythms is the lack of understanding of the cellular and network level generators of these macroscopic scale signals. We are addressing this challenge by designing biophysically principled models of neocortical circuits that are uniquely designed to simulate MEG/EEG measured activity based on the underlying electromagnetic physics. We are employing these models to study the mechanisms and functions of low frequency rhythms and validating our predictions with invasive recordings in animals and humans, through collaboration. In this talk, I will describe how our methods have led to a novel hypothesis on the neural origin of beta frequency rhythms (15-29Hz). We have shown that spontaneous beta rhythms from human somatosensory cortex predict perception, are modulated with attention and increase with healthy aging and our model is providing a mechanistic link between beta and such functions. Specifically, our data show that neocortical beta activity emerges transiently (typically lasting <200ms). Our model predicts that such beta “transients” emerge from the integration of synchronous bursts of excitatory synaptic drive targeting proximal and distal pyramidal neuron dendrites, such that the distal drive is necessarilystronger and lasted one beta period. I will present data from invasive laminar local field potential recordings in mice and monkeys that support this beta hypothesis, and will describe ongoing efforts to test the hypothesis with invasive recordings in human patients. Lastly, I will discuss our ongoing efforts and ideas to apply our methods to design transcranial electrical current stimulation paradigms that are optimized to manipulate low frequency rhythms to improve brain function.

Holly Lisanby, MD (Duke Institute for Brain Sciences)

Title: Enhancement of cognitive performance with TMS and other neuromodulatory techniques; gaps and opportunities.

Earl Miller, PhD (Massachusetts Institute of Technology)

Title: Cognition is Rhythmic: implications for brain stimulation

Abstract: How are some thoughts favored over others? More generally, how is thought coordinated and directed toward goals? Mounting evidence suggests that this arises from interactions between widespread cortical and subcortical networks that may be regulated via their rhythmic synchronization. This could extend to all cognitive processes, suggesting our brain does not operate continuously, but rather discretely, with pulses of activity routing packets of information. Such discrete cycles would provide a backbone for coordinating computations (and their results) across disparate networks. I will discuss evidence and the possibility of modifying cognitive function by modulating these rhythms.

Read Montague, PhD (Virginia Tech Carilion Research Institute)

Title: A mélange of errors: sub-second dopamine fluctuations in human striatum encode superposed error signals about actual and counterfactual reward

Abstract: In the mammalian brain, dopamine is a critical neuromodulator whose downstream actions underlie prediction learning, decision-making, and behavioral control. Degeneration of dopamine neurons causes Parkinson’s disease while dysregulation of dopamine signaling is believed to contribute to numerous psychiatric conditions such as schizophrenia, addiction, and depression. Experiments in animal models support the hypothesis that dopamine release in human striatum encodes reward   prediction errors during ongoing decision-making. Blood- oxygen-level-dependent (BOLD) imaging experiments in humans support the idea that these errors are tracked by neural responses in the striatum. However, BOLD measurements cannot be used to infer the action of any one specific neurotransmitter. We monitored dopamine levels with sub-second temporal resolution in humans (N=17) with Parkinson’s disease while they executed a sequential decision-making task. Participants placed bets and experienced monetary gains or losses. Dopamine fluctuations in the striatum fail to encode reward prediction errors as anticipated by a large body of work in model organisms. Instead, sub-second dopamine fluctuations encode an integration of reward prediction errors with counterfactual prediction errors; the latter defined by how much better or worse the experienced outcome could have been. These results have implications for the kinds of information thought to be carried by dopamine delivery.

Lucas Parra, PhD (The City College of New York)

Title: Cellular and network effects of transcranial electrical stimulation with weak currents

Abstract: Transcranial electric stimulation with weak currents (TES, ~1mA) has emerged as a promising tool for modulating brain function in therapeutic and research settings. However, the efficacy of TES remains controversial in part because the electric fields generated in the brain are relatively small (<1V/m) and the mechanisms of action not well understood. We and others have shown through in vitro experiments and computational models that electric fields can modulate firing rate, spike timing and synaptic efficacy by weakly polarizing neuronal membranes (<1mV). Now we are investigating how these acute effects translate into long-term changes in neuronal function, which are the primary endpoint for most human TES studies. Our latest in-vitro results demonstrate that field-induced membrane polarization can modulate synaptic long-term potentiation and depression. The specific results do not support the conventional view adopted in many clinical studies that stimulation polarity determines whether neuronal excitability is increased or decreased and instead we see an overall trend towards potentiation. Understanding the basic mechanism of how weak current stimulation affect neuronal activity is thus crucial for the rational design of neuromodulation studies in clinical research and basic neuroscience.

Josef Parvizi, MD, PhD (Stanford School of Medicine)

Title: Exploring the spatiotemporal dynamics of functional networks in the human brain using a multimodal approach

Abstract:Combining intracranial EEG with functional imaging and direct cortical stimulation in individual human subjects make it possible to obtain simultaneous electrophysiological recordings from pre-identified nodes of functional networks in the human brain, and do so with a high anatomical precision and temporal resolution while electrically perturbing the dynamics of activity in the network to test the causal role of, and directionality of information flow within the network. This presentation will present prototype examples of how this multimodal approach can provide novel insights about spatiotemporal dynamics of functional networks in the human brain. 

Steven Schiff, MD, PhD (Pennsylvania State University)

Title: Unification of Neuronal Spikes, Seizures, and Spreading Depression 

Abstract: By incorporating conservation of particles and charge, and accounting for the energy required to restore ionic gradients, we extend the classic Hodgkin–Huxley formalism to uncover a unification of neuronal membrane dynamics. By examining the dynamics as a function of potassium and oxygen, we now account for a wide range of neuronal activities, from spikes to seizures, spreading depression (whether high potassium or hypoxia induced), mixed seizure and spreading depression states, and the terminal anoxic “wave of death.” Such a unified framework demonstrates that all of these dynamics lie along a continuum of the repertoire of the neuron membrane.  By more fully accounting for charge carriers, conservation of mass in such models opens the prospect of modeling 'conservative stimulation,' offering a more physiologically realistic understanding of the interaction between stimulation and brain activity modulation. In addition, accounting for energy balance in neurons enables us to account for the energy load placed on neurons during brain stimulation. Our results demonstrate that unified frameworks for neuronal dynamics are feasible, can be achieved using existing biological structures and universal physical conservation principles, and may be of substantial importance in enabling our understanding of brain activity and its response to stimulation.

Vikaas Sohal, MD, PhD (University of California, San Francisco)

Title: Inhibitory neuron-generated gamma oscillations regulate cognitive flexibility in mice

Abstract: Gamma oscillations are generated by parvalbumin (PV) interneurons, and frequently observed during cognitive tasks, however their significance for these tasks remains unclear. This is an important issue in the context of disorders such as schizophrenia, in which markers for PV interneurons as well as gamma oscillations themselves are both abnormal. I will describe a recent project from my laboratory which studied mice that model the abnormalities in PV interneurons, gamma oscillations, and cognitive flexibility seen in schizophrenia. In these mice, optogenetically restoring interneuron-driven gamma oscillations in the prefrontal cortex leads to long-lasting improvements in cognition. If there is time, I will also outline work my lab is doing as part of the DARPA SUBNETS project, studying ECoG recordings from human patients with epilepsy, in order to identify changes in rhythmic network activity associated with depression and anxiety.

Joel Voss, PhD (Northwestern University Feinberg School of Medicine)

Title: Nonsurgical stimulation targeting hippocampal networks and memory in humans

Abstract: Episodic memory has been associated with interactions among a distributed set of brain regions forming a hippocampal-cortical network. This network is disrupted in a variety of neurological and neuropsychiatric conditions that have memory impairment as a chief symptom. I will describe my laboratory's efforts to target and manipulate portions of this network using nonsurgical electromagnetic stimulation. We have shown that multiple-day, network-targeted, repetitive transcranial magnetic stimulation (rTMS) can produce lasting enhancements of network functional MRI connectivity and episodic memory performance. These changes are robust 24 hours after the final rTMS session and persist in weakened form for up to 2 weeks. Furthermore, rTMS-induced changes are highly specific to targeted portions of the hippocampal-cortical network defined a priori on anatomical grounds. Improvements in episodic memory performance also occur with enhanced neural correlates of recollective retrieval, suggesting relative specificity of stimulation effects on the targeted posterior portions of the hippocampal-cortical network that are more heavily implicated in recollective than familiarity-based memory retrieval. Targeted nonsurgical stimulation of hippocampal-cortical networks is a promising approach for studying involvement of hippocampal-cortical networks in memory that could have significant impact on impairments of memory in a variety of disorders.

Xiao-Jing Wang, PhD (New York University)

Title: Frequency-dependent inter-areal interaction in a large-scale circuit model of the primate cortex

Abstract: We propose that the mechanism of brain stimulation requires an understanding of how perturbations at different frequencies affect differentially feedforward and feedback information flow along the brain hierarchy. To test this idea, we incorporated laminar-dependent inter-areal connectivity in a large-scale dynamical model of the monkey cortex endowed with weighted and directed connectivity. Each cortical area is modeled with a superficial layer and a deep layer. Based on recent physiological evidence, we modeled excitatory and inhibitory neural populations in each layer, with local properties that generate noise-driven gamma oscillations in the superficial layer and alpha oscillations in the deep layer. Furthermore, the superficial-to-deep projection is dominated by excitation whereas the deep-to-superficial feedback is primarily inhibitory. We calibrated the model by simulating physiological observations that feedforward interactions are associated with oscillations in the gamma band (50-80Hz), while feedback interactions relate to lower frequencies, in the alpha or low beta frequency range (8-20 Hz). Using Granger causality to establish the directionality of information flow, the model reproduces the observed hierarchical order of visual areas at the functional level (Bastos et al. Neuron 2014). The model identifies several properties of feedback projections as key factors to explain these hierarchical dynamics, in particular the relative weights of a feedback projection onto the superficial versus deep layer in a target area. This quantitative model provides a platform for investigating the rich dynamics of the primate large-scale cortical system, and the physiological basis of weak frequency-dependent electromagnetic stimulation in the brain.

Alik Widge, MD, PhD (Massachusetts General Hospital)

Title: Network-Level Changes from Subcortical Brain Stimulation: Lessons Learned and Implications for Non-Invasive Technologies

Abstract: Deep brain stimulation (DBS), generally delivered at frequencies in excess of 100 Hz, is believed to break reverberant cortical-subcortical oscillatory loops. There is evidence for this theory in Parkinson’s disease, but it has been only partly tested in psychiatric disorders. I will discuss two lines of work from our laboratory and collaborations that seek to better understand the effects of oscillatory subcortical stimulation on cortical rhythms. First, I will present emerging results from our ongoing studies of top-down control in patients with ventral capsule/ventral striatum (VC/VS) DBS, including evidence that this stimulation specifically affects oscillatory dynamics in prefrontal cortex. Second, I will show emerging results from the TRANSFORM DBS program, where we are developing statistical and biophysical models to predict a network’s response to stimulation at a single node. In both cases, stimulation at a subcortical site has marked cortical effects, suggesting that we may be able to replicate the result by carefully engineering a non-invasive protocol.

Theodore Zanto, PhD (University of California, San Francisco)

Title: Individual differences in TMS effects: From functional connectivity to functional recruitment

Abstract: The effects of transcranial magnetic stimulation (TMS) may vary widely based on the selected TMS parameters, such as intensity, duration, and frequency of stimulation. Furthermore, the structural and functional architecture of the participant as well as their cognitive state during stimulation may also affect TMS outcomes. Here, data across several experiments will be presented to highlight individual differences in TMS effects. Results indicate that opposing TMS effects may be observed based on 1) the functional connectivity strength in the stimulated network, 2) the extant of functional connectivity in the stimulated network, 3) the instantaneous phase of cortical oscillations at the site of stimulation and 4) an ability to recruit compensatory cortical regions following neural perturbation. Together, individual differences in response to TMS may be better accounted for by a precise characterization of the individual’s instantaneous functional architecture at the onset of stimulation as well as the individual’s capacity for neuroplasticity.