Bijan Pesaran

• PhD
• Professor at New York University

Introduction: Treatment–refractory obsessive–compulsive disorder (trOCD) is a complex brain network disorder that remains partially understood and may require personalized treatment strategies due to disease heterogeneity. While stereo–electroencephalography (sEEG) is standard of care for surgical epilepsy workups, its use in refractory neuropsychi...

INTRODUCTION Subthalamic Nucleus Deep Brain Stimulation (STN-DBS) in Parkinson’s Disease (PD) involves disruption of motor cortex-STN synchrony of beta-band oscillations. However, precise neural substrates within the motor cortex where such oscillatory fluctuations and their interactions occur are still unknown. Understanding spatial-temporal dynam...

INTRODUCTION The advancement of brain-computer interfaces (BCIs) is contingent on our capability to accurately decode neural signals. The recent development of novel high-density surface electrode arrays will facilitate the capture of more nuanced neural activations, enhancing our understanding of cortical functions. However, there is a need to dev...

INTRODUCTION Understanding dynamic neural activity in the motor cortex during movement is crucial for neurological treatment, rehabilitation, and brain-computer interfaces. The relationship between spatially distributed brain activity and precise arm and hand movement control is key to understanding motor function. However, observing these dynamics...

Nonlinear mixed selectivity, with neurons responding to diverse combinations of task-relevant variables, has been proposed as a key mechanism to enable flexible behavior and cognition. However, it is debated whether the structure of neural population responses in fronto-parietal cortices is better described as random mixed-selective or as non-rando...

Electrical stimulation of the brain is being developed as a treatment for an increasing number of neurological disorders. Technologies for delivering electrical stimulation are advancing rapidly and vary in specificity, coverage, and invasiveness. Supracortical microstimulation (SCMS), characterized by microelectrode contacts placed on the epidural...

Substance use disorders (SUDs) are a significant public health concern, with over 30% failing available treatment. Severe SUD is characterized by drug-cue reactivity that predicts treatment-failure. We leveraged this pathophysiological feature to personalize deep brain stimulation (DBS) of the nucleus accumbens region (NAc) in an SUD patient. While...

Understanding the dynamical transformation of neural activity to behavior requires new capabilities to nonlinearly model, dissociate and prioritize behaviorally relevant neural dynamics and test hypotheses about the origin of nonlinearity. We present dissociative prioritized analysis of dynamics (DPAD), a nonlinear dynamical modeling approach that...

Optical neurotechnologies use light to interface with neurons and can monitor and manipulate neural activity with high spatial-temporal precision over large cortical areas. There has been considerable progress in miniaturizing microscopes for head-mounted configurations, but existing devices are bulky and their application in humans will require a...

Traumatic brain injury (TBI) remains a pervasive clinical problem associated with significant morbidity and mortality. However, TBI remains clinically and biophysically ill-defined, and prognosis remains difficult even with the standardization of clinical guidelines and advent of multimodality monitoring. Here we leverage a unique data set from TBI...

Minimally invasive, high-bandwidth brain-computer-interface (BCI) devices can revolutionize human applications. With orders-of-magnitude improvements in volumetric efficiency over other BCI technologies, we developed a 50-μm-thick, mechanically flexible micro-electrocorticography (μECoG) BCI, integrating 256×256 electrodes, signal processing, data...

The detection of events in time-series data is a common signal-processing problem. When the data can be modeled as a known template signal with an unknown delay in Gaussian noise, detection of the template signal can be done with a traditional matched filter. However, in many applications, the event of interest is represented in multimodal data con...

Objective. Learning dynamical latent state models for multimodal spiking and field potential activity can reveal their collective low-dimensional dynamics and enable better decoding of behavior through multimodal fusion. Toward this goal, developing unsupervised learning methods that are computationally efficient is important, especially for real-t...

The detection of events in time-series data is a common signal-processing problem. When the data can be modeled as a known template signal with an unknown delay in Gaussian noise, detection of the template signal can be done with a traditional matched filter. However, in many applications, the event of interest is represented in multimodal data con...

Modelling the spatiotemporal dynamics in the activity of neural populations while also enabling their flexible inference is hindered by the complexity and noisiness of neural observations. Here we show that the lower-dimensional nonlinear latent factors and latent structures can be computationally modelled in a manner that allows for flexible infer...

Neuromodulatory interventions seek to treat neuropsychiatric disorders by manipulating multiregional communication across the mesolimbic mood network. Modulations of multiregional communication are rarely measured directly and are often inferred from correlated neural activity such as neural coherence. Whether and how neural coherence reflects dyna...

Salience-driven exogenous and goal-driven endogenous attentional selection are two distinct forms of attention that guide selection of task-irrelevant and task-relevant targets in primates. Top-down attentional control mechanisms enable selection of the task-relevant target by limiting the influence of sensory information. Although the lateral pref...

Learning dynamical latent state models for multimodal spiking and field potential activity can reveal their collective low-dimensional dynamics and enable better decoding of behavior through multimodal fusion. Toward this goal, developing unsupervised learning methods that are computationally efficient is important, especially for real-time learnin...

Objective Effective surgical treatment of drug‐resistant epilepsy depends on accurate localization of the epileptogenic zone (EZ). High‐frequency oscillations (HFOs) are potential biomarkers of the EZ. Previous research has shown that HFOs often occur within submillimeter areas of brain tissue and that the coarse spatial sampling of clinical intrac...

In the reach and saccade regions of the posterior parietal cortex (PPC), multiregional communication depends on the timing of neuronal activity with respect to beta-frequency (10-30 Hz) local field potential (LFP) activity, termed dual coherence. Neural coherence is believed to reflect neural excitability, whereby spiking tends to occur at a partic...

Inferring complex spatiotemporal dynamics in neural population activity is critical for investigating neural mechanisms and developing neurotechnology. These activity patterns are noisy observations of lower-dimensional latent factors and their nonlinear dynamical structure. A major unaddressed challenge is to model this nonlinear structure, but in...

Optical neurotechnologies use light to interface with neurons and can monitor and manipulate neural activity with high spatial-temporal precision over large cortical extents. While there has been significant progress in miniaturizing microscope for head-mounted configurations, these existing devices are still very bulky and could never be fully imp...

Salience-driven exogenous and goal-driven endogenous attentional selection are two distinct forms of attention that guide selection of task-irrelevant and task-relevant targets in primates. During conflict i.e, when salience and goal each favor the selection of different targets, endogenous selection of the task-relevant target relies on top-down c...

Objective. Realizing neurotechnologies that enable long-term neural recordings across multiple spatial-temporal scales during naturalistic behaviors requires new modeling and inference methods that can simultaneously address two challenges. First, the methods should aggregate information across all activity scales from multiple recording sources su...

Objective: Neural dynamical models reconstruct neural data using dynamical systems. These models enable direct reconstruction and estimation of neural time-series data as well as estimation of neural latent states. Nonlinear neural dynamical models using recurrent neural networks in an encoder-decoder architecture have recently enabled accurate sin...

Objective. The force that an electrocorticography (ECoG) array exerts on the brain manifests when it bends to match the curvature of the skull and cerebral cortex. This force can negatively impact both short-term and long-term patient outcomes. Here we provide a mechanical characterization of a novel liquid crystal polymer (LCP) ECoG array prototyp...

Realizing neurotechnologies that enable long-term neural recordings across multiple spatial-temporal scales during naturalistic behaviors requires new modeling and inference methods that can simultaneously address two challenges. First, the methods should aggregate information across all activity scales from multiple recording sources such as spiki...

One-third of epilepsy patients suffer from medication-resistant seizures. While surgery to remove epileptogenic tissue helps some patients, 30–70% of patients continue to experience seizures following resection. Surgical outcomes may be improved with more accurate localization of epileptogenic tissue. We have previously developed novel thin-film, s...

Looking and reaching are controlled by different brain regions and are coordinated during natural behaviour¹. Understanding how flexible, natural behaviours such as coordinated looking and reaching are controlled depends on understanding how neurons in different regions of the brain communicate². Neural coherence in a gamma-frequency (40–90 Hz) ban...

Objective. Brain recordings exhibit dynamics at multiple spatiotemporal scales, which are measured with spike trains and larger-scale field potential signals. To study neural processes, it is important to identify and model causal interactions not only at a single scale of activity, but also across multiple scales, i.e. between spike trains and fie...

One-third of epilepsy patients suffer from medication-resistant seizures. While surgery to remove epileptogenic tissue helps some patients, 30-70% of patients continue to experience seizures following resection. Surgical outcomes may be improved with more accurate localization of epileptogenic tissue. We have previously developed novel thin-film, s...

Understanding the dynamical transformation of neural activity to behavior requires modeling this transformation while both dissecting its potential nonlinearities and dissociating and preserving its nonlinear behaviorally relevant neural dynamics, which remain unaddressed. We present RNN PSID, a nonlinear dynamic modeling method that enables flexib...

Objective. Brain functions such as perception, motor control, learning, and memory arise from the coordinated activity of neuronal assemblies distributed across multiple brain regions. While major progress has been made in understanding the function of individual neurons, circuit interactions remain poorly understood. A fundamental obstacle to deci...

Non-parametric regression has been shown to be useful in extracting relevant features from Local Field Potential (LFP) signals for decoding motor intentions. Yet, in many instances, brain-computer interfaces (BCIs) rely on simple classification methods, circumventing deep neural networks (DNNs) due to limited training data. This paper leverages the...

Direct electrical stimulation can modulate the activity of brain networks for the treatment of several neurological and neuropsychiatric disorders and for restoring lost function. However, precise neuromodulation in an individual requires the accurate modelling and prediction of the effects of stimulation on the activity of their large-scale brain...

Emerging technologies to acquire data at increasingly greater scales promise to transform discovery in systems neuroscience. However, current exponential growth in the scale of data acquisition is a double-edged sword. Scaling up data acquisition can speed up the cycle of discovery but can also misinterpret the results or possibly slow down the cyc...

Objective. Large channel count surface-based electrophysiology arrays (e.g. µECoG) are high-throughput neural interfaces with good chronic stability. Electrode spacing remains ad hoc due to redundancy and nonstationarity of field dynamics. Here, we establish a criterion for electrode spacing based on the expected accuracy of predicting unsampled fi...

Motor function depends on neural dynamics spanning multiple spatiotemporal scales of population activity, from spiking of neurons to larger-scale local field potentials (LFP). How multiple scales of low-dimensional population dynamics are related in control of movements remains unknown. Multiscale neural dynamics are especially important to study i...

Neural activity exhibits complex dynamics related to various brain functions, internal states and behaviors. Understanding how neural dynamics explain specific measured behaviors requires dissociating behaviorally relevant and irrelevant dynamics, which is not achieved with current neural dynamic models as they are learned without considering behav...

Multiregional communication is important to understanding the brain mechanisms supporting complex behaviors. Work in animals and human subjects shows that multiregional communication plays significant roles in cognitive function and is associated with neurological and neuropsychiatric disorders of brain function. Recent experimental advances enable...

Neural-Matrix style, high-density electrode arrays for brain-machine interfaces (BMIs) and neuroscientific research require the use of multiplexing: Each recording channel can be routed to one of several electrode sites on the array. This capability allows the user to flexibly distribute recording channels to the locations where the most desirable...

In this paper, we demonstrate that a neural decoder trained on neural activity signals of one subject can be used to \textit{robustly} decode the motor intentions of a different subject with high reliability. This is achieved in spite of the non-stationary nature of neural activity signals and the subject-specific variations of the recording condit...

Neural decoding and neuromodulation technologies hold great promise for treating mood and other brain disorders in next-generation therapies that manipulate functional brain networks. Here we perform a novel causal network analysis to decode multiregional communication in the primate mood processing network and determine how neuromodulation, short-...

Understanding how natural behaviors are controlled depends on understanding the neural mechanisms of multiregional communication. Eye-hand coordination, a natural behavior shared by primates, is controlled by the posterior parietal cortex (PPC), a brain structure that expanded substantially in primate evolution. Here, we show that neurons within th...

Long-lasting, high-resolution neural interfaces that are ultrathin and flexible are essential for precise brain mapping and high-performance neuroprosthetic systems. Scaling to sample thousands of sites across large brain regions requires integrating powered electronics to multiplex many electrodes to a few external wires. However, existing multipl...

Objective. We consider the cross-subject decoding problem from local field potential (LFP) signals, where training data collected from the prefrontal cortex (PFC) of a source subject is used to decode intended motor actions in a destination subject. Approach. We propose a novel supervised transfer learning technique, referred to as data centering,...

Coherent neuronal dynamics play an important role in complex cognitive functions. Optogenetic stimulation promises to provide new ways to test the functional significance of coherent neural activity. However, the mechanisms by which optogenetic stimulation drives coherent dynamics remain unclear, especially in the nonhuman primate brain. Here, we p...

Synopsis The visual system has evolved to help guide behavior. In primates, a network of brain areas work together to orchestrate eye, hand, and limb movements with precise spatial and temporal precision. Here we review the extensive behavioral and neurophysiological literature that has contributed to our understanding of how visual information is...

Objective. We consider the cross-subject decoding problem from local field potential (LFP) activity, where training data collected from the pre-frontal cortex of a subject (source) is used to decode intended motor actions in another subject (destination). Approach. We propose a novel pre-processing technique, referred to as data centering, which is...

Experts review the latest research on the neocortex and consider potential directions for future research. Over the past decade, technological advances have dramatically increased information on the structural and functional organization of the brain, especially the cerebral cortex. This explosion of data has radically expanded our ability to chara...

Objective. Information encoding in neurons can be described through their response fields. The spatial response field of a neuron is the region of space in which a sensory stimulus or a behavioral event causes that neuron to fire. Neurons can also exhibit temporal response fields (TRFs), which characterize a transient response to stimulus or behavi...

Neural activity exhibits dynamics that in addition to a behavior of interest also relate to other brain functions or internal states. Understanding how neural dynamics explain behavior requires dissociating behaviorally relevant and irrelevant dynamics, which is not achieved with current neural dynamic models as they are learned without considering...

Objective. Behavior is encoded across multiple scales of brain activity, from binary neuronal spikes to continuous fields including local field potentials (LFP). Multiscale models need to describe both the encoding of behavior and the conditional dependencies in simultaneously recorded spike and field signals, which form a high-dimensional multisca...

Neural decoding and neuromodulation technologies hold great promise for treating mood and other brain disorders in next-generation therapies that manipulate functional brain networks. Here, we perform a novel causal network analysis to decode multiregional communication in the primate mood processing network and determine how neuromodulation, short...

Objective. We consider the problem of predicting eye movement goals from local field potentials (LFP) recorded through a multielectrode array in the macaque prefrontal cortex. The monkey is tasked with performing memory-guided saccades to one of eight targets during which LFP activity is recorded and used to train a decoder. Approach. Previous repo...

Significance Previous work in humans has found rhythmic cortical activity while listening to rhythmic sounds such as speech or music. Whether this activity reflects oscillatory dynamics of a neural circuit or instead evoked responses to the rhythmic stimulus has been difficult to determine. Here, we devised a metric to tease apart the two hypothese...

We consider the problem of predicting eye movement goals from local field potentials (LFP) recorded through a multielectrode array in the macaque prefrontal cortex. The monkey is tasked with performing memory-guided saccades to one of eight targets during which LFP activity is recorded and used to train a decoder. Previous reports have mainly relie...

Objective. Behavior is encoded across multiple spatiotemporal scales of brain activity. Modern technology can simultaneously record various scales, from spiking of individual neurons to large neural populations measured with field activity. This capability necessitates developing multiscale modeling and decoding algorithms for spike-field activity,...

Economic decisions can adapt to contexts. Choices can be quick and impulsive or slow and more deliberative, depending on the temporal context. Choices can also depend on how we enact the choice, in an action context. Where we decide to go for dinner may change if we can take a taxi or need to walk. We hypothesized that frontal action circuits could...

Optogenetic stimulation offers powerful new ways to test the functional significance of coherent neuronal activity. In rodents, optogenetically stimulating specific classes of neurons has been shown to selectively perturb coherent neuronal dynamics. Testing the causal role of coherent neuronal dynamics for complex cognitive functions requires studi...

Neural circuitry can be investigated and manipulated using a variety of techniques, including electrical and optical recording and stimulation. At present, most neural interfaces are designed to accommodate a single mode of neural recording and/or manipulation, which limits the amount of data that can be extracted from a single population of neuron...

The size and curvature of the macaque brain present challenges for two photon laser scanning microscopy (2P-LSM). General access to the cortex requires 5-axis positioning over a range of motion wider than existing designs offer. In addition, movement artifacts due to physiological pulsations and bodily movement present particular challenges. We pre...

A key element needed in a brain-machine interface (BMI) decoder is the encoding model, which relates the neural activity to intended movement. The vast majority of work have used a representational encoding model, which assumes movement parameters are directly encoded in neural activity. Recent work have in turn suggested the existence of neural dy...

New technologies to record electrical activity from the brain on a massive scale offer tremendous opportunities for discovery. Electrical measurements of large-scale brain dynamics, termed field potentials, are especially important to understanding and treating the human brain. Here, our goal is to provide best practices on how field potential reco...

A macaque monkey is trained to perform two different kind of tasks, memory aided and visually aided. In each task, the monkey saccades to eight possible target location. A classifier is proposed for direction decoding and task decoding based on local field potentials (LFP) collected from the prefrontal cortex. The LFP time-series data is modeled in...

A problem of classification of local field potentials (LFPs), recorded from the prefrontal cortex of a macaque monkey, is considered. An adult macaque monkey is trained to perform a memory based saccade. The objective is to decode the eye movement goals from the LFP collected during a memory period. The LFP classification problem is modeled as that...

Brain-machine interfaces (BMIs) define new ways to interact with our environment and hold great promise for clinical therapies. Motor BMIs, for instance, re-route neural activity to control movements of a new effector and could restore movement to people with paralysis. Increasing experience shows that interfacing with the brain inevitably changes...

Reaching is an essential behavior that allows primates to interact with the environment. Precise reaching to visual targets depends on our ability to localize and foveate the target. Despite this, how the saccade system contributes to improvements in reach accuracy remains poorly understood. To assess spatial contributions of eye movements to reach...

Recordings from invasive implants can degrade over time, resulting in a loss of spiking activity for some electrodes. For brain-machine interfaces (BMI), such a signal degradation lowers control performance. Achieving reliable performance over time is critical for BMI clinical viability. One approach to improve BMI longevity is to simultaneously us...

Verbal working memory (vWM) involves storing and manipulating information in phonological sensory input. An influential theory of vWM proposes that manipulation is carried out by a central executive while storage is performed by two interacting systems: a phonological input buffer that captures sound-based information and an articulatory rehearsal...

Significance A central question in systems neuroscience is how cognitive functions can arise from the interplay of many different brain areas. For example the cognitive act of forming a decision requires a concerted computation involving sensory, mnemonic, and executive information residing in neural circuits that have different anatomical location...

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The development of novel neurotechnologies for treating refractory neuropsychiatry disorders depends on understanding and manipulating the dynamics of neural circuits across large-scale brain networks. The mesolimbic pathway plays an essential role in reward processing and mood regulation and disorders of this pathway underlie many neuropsychiatric...

Background: Video-based noninvasive eye trackers are an extremely useful tool for many areas of research. Many open-source eye trackers are available but current open-source systems are not designed to track eye movements with the temporal resolution required to investigate the mechanisms of oculomotor behavior. Commercial systems are available bu...

Determining a person’s intent, such as the planned direction of their movement, directly from their cortical activity could support important applications such as brain-computer interfaces (BCIs). Continuing development of improved BCI systems requires a better understanding of how the brain prepares for and executes movements. To contribute to thi...

Selecting and planning actions recruits neurons across many areas of the brain, but how ensembles of neurons work together to make decisions is unknown. Temporally coherent neural activity may provide a mechanism by which neurons coordinate their activity to make decisions. If so, neurons that are part of coherent ensembles may predict movement cho...

Significance Human cognition depends on the brain’s ability to remember and manipulate information about recent experience. Although this working memory ability has been linked with the persistent spiking activity of neurons in prefrontal cortex (PFC), the population-scale organization of working memory in this region remains poorly understood. Her...

The brain operates on many different scales, from individual neurons to interacting cortical areas. Similarly, electrophysiology can monitor neural activity at a variety of spatial resolutions. Yet the majority of electrophysiology studies focus on a single scale of measurements. Simultaneously monitoring neural activity at multiple spatial scales...

Prosthetic devices, methods and systems are disclosed. Eye position and/or neural activity of a primate are recorded and combined. The combination signal is compared with a predetermined signal. The result of the comparison step is used to actuate the prosthetic device.

Historically, the study of speech processing has emphasized a strong link between auditory perceptual input and motor production output. A kind of 'parity' is essential, as both perception- and production-based representations must form a unified interface to facilitate access to higher-order language processes such as syntax and semantics, believe...

A major challenge facing the development of high degree of freedom (DOF) brain machine interface (BMI) devices is a limited ability to provide prospective users with independent control of many DOFs when using a complex prosthesis. It has been previously shown that a large range of complex hand postures can be replicated using a relatively low numb...

A major goal for brain machine interfaces is to allow patients to control prosthetic devices with high degrees of independent movements. Such devices like robotic arms and hands require this high dimensionality of control to restore the full range of actions exhibited in natural movement. Current BMI strategies fall well short of this goal allowing...