CCNP Meetings

Phil Corlett
Department of Psychiatry
Yale University

Psychosis is generally defined in terms experiences that deviate appreciably from consensual reality. I will discuss two of its component symptoms; anomalous perceptions (“hallucinations”) and bizarre and inexplicable beliefs (“delusions”). A major challenge in developing a coherent understanding of psychosis is to characterize the disturbances that may give rise both to profoundly altered experiences and to impairments in belief. I will explore the degree to which understanding the brain as a predictive inference device may help us explain psychotic symptoms. I will argue that hallucinations and delusions may arise and be maintained as a result of aberrant prediction errors which garner strong top-down priors as palliative explanatory responses. By refining our understanding of how these disturbances may occur, we gain valuable insights to how the brain generates our experiences more generally.

Philipp Sterzer
Professor of Psychiatry and Computational Neuroscience
Charité – Universitätsmedizin Berlin

Perceptual inference is the process by which current beliefs are used to infer the probable causes of the incoming sensory signals. When these sensory signals are perceptually ambiguous, inference may result in spontaneous alterations between two or more perceptual states, a phenomenon called multistable perception. The neural mechanisms of the underlying inferential process have remained controversial. Whereas some authors argue that multistable perception is governed by local processes in sensory cortices, others have proposed a role for higher-level frontoparietal brain regions in driving perceptual inference. Here, I will propose an account of multistable perception that can reconcile these apparently contradictory views within the computational framework of predictive coding. I will also present results from computational modeling in a Bayesian framework and model-based fMRI that support the proposed account. Finally, I will outline how altered predictive coding may explain abnormal inference in psychotic states and present empirical behavioral and neuroimaging work that used multistable perception to probe the role of predictive feedback signaling in psychosis.

Jordan Hamm
Department of Biological Sciences
Columbia University

While prefrontal cortex and brain-wide, interregional networks are often studied in major neurological and psychiatric disorders, synaptic and cell-type specific pathophysiology has been identified in nearly all cortical areas in diseases like schizophrenia (SZ), suggesting that neuronal circuit function at the most basic level could play a critical role. Two-photon calcium imaging (2P-Ca++) studies in rodents have shown that local neuron populations in neocortical circuits (<1mm3) display distinct activity patterns made up of coactive “ensembles”, a level of detailed dynamics not captured by gross level (EEG, fMRI) or single neuron recordings. These activity patterns repeat during basic sensory and cognitive processing and also spontaneously at rest, suggesting that they make up the preferred, semi-stable “attractor” states of the cortex. Here I present findings from distinct mouse models of SZ-relevant disease processes (NMDA-receptor block, 22q11.2 microdeletion) that support the notion that a disorganization of local ensembles and the underlying “attractor” landscape could underlie basic perceptual and cognitive deficits in the disease. Interestingly, while acute manipulations of excitation, inhibition, or top-down inputs recreated cortical processing abnormalities at the single neuron level, key deficits in population-level synchrony patterns were only observed after chronic disease-relevant manipulations or in genetic models. Implications and future approaches for understanding and targeting altered synaptic plasticity processes across key neurodevelopmental periods will be discussed.

Travis Baker
Rutgers Center for Molecular and Behavioral Neuroscience
Rutgers University

Neurocognitive alterations to mesocorticolimbic reward function by drugs of abuse are thought to facilitate a progression towards excessive drug use. Despite efforts to identify methods to counteract such drug-induced neural alterations, brain-based treatments for this disorder remain underdeveloped and often ineffective. In this talk, I propose that the anterior cingulate cortex (ACC) putative function—selecting and motivating the execution of extended goal-directed behaviors—can be utilized as a biomarker for the abnormal reward processes underlying substance misuse. I will present support for this proposal utilizing the reward positivity as a quantifiable EEG metric of reward-related ACC function. First, people who abuse addictive substances produce a relatively small reward positivity to monetary incentives, and that this impairment is modulated by a genetic polymorphism that codes for the expression of dopamine D4 receptors. Second, drug rewards (puffs of a cigarette) elicit a relatively larger reward positivity than nondrug rewards (money) in abstinent smokers. Third, applying excitatory or inhibitory stimulation to a subject-specific frontal-cingulate reward pathway using robot-assisted fMRI-guided rTMS can alter the amplitude of the reward positivity elicited by drug and non-drug rewards. In sum, our efforts point to a decisive role of integrating multimodal neuroimaging methods as an early stage in treatment development for substance use disorders, with a highly sensitive EEG-based biomarker of addiction severity and treatment efficacy.

Emanuel Bubl
Department of Psychiatry and Psychotherapy
Albert-Ludwigs-University of Freiburg

The presentation evaluates the potential of visual contrast processing as a neurobiological correlate for depression and attention deficit hyperactivity disorder (ADHD) by targeting two questions:
1. the relevance of the findings in depression and ADHD compared to other disorders.
2. the distinct impact of treatment on these very early signals.

Prantik Kundu
Departments of Radiology and Psychiatry
Icahn School of Medicine at Mount Sinai

The past 25 years of neuroscientific research with functional MRI has shown in detail the functional and connectomic organization of the human cerebral cortex. However, the interactions of the cortex with the subcortex have been more challenging to evaluate in vivo due to poor fMRI signal from subcortical regions. This is a major issue since poor signal fidelity from areas such as striatum, thalamus, and the midbrain limits the progress for understanding neuropsychiatric disease. We addressed this issue by developing the fMRI approach called multi-echo multi-band (MEMB)-fMRI. By using a modified echo planar imaging (EPI) sequence that implements T2* relaxometry alongside BOLD imaging, MEMB-fMRI increases BOLD contrast and mitigates non-BOLD artifact to enhance detection of subcortical-cortical activation and connectivity. After reviewing MEMB-fMRI methodology, we will discuss our recent findings on: frontostriatal connectivity, thalamocortical dysconnectivity in psychosis using 7 T MRI; and activation and connectivity in arousal circuitry including the locus coeruleus based on the NPU threat task.

Anna Konova
Center for Neural Science
New York University

The symptoms of drug addiction imply alterations in decision processes. The integrative field of neuroeconomics, which borrows concepts and methods from economics, psychology, and neuroscience, has identified a “domain general” neural system encompassing the ventromedial prefrontal cortex and the striatum in the computation of subjective value – the basis of idiosyncratic preferences and choice. Indeed, the application of this framework to addiction in both humans and other animals has successfully captured many features of addiction. However, this work has generally considered addiction as a static entity, ignoring addiction’s most elusive (and perhaps most defining) feature – its stereotyped, cyclic nature at the level of the individual, characterized by alternating periods of abstinence and drug use. I will discuss ongoing work in which we aim to better understand two dynamic processes at the transition between abstinence and relapse to drug use: (1) a relatively slower process (in the order of weeks and months) related to risk preferences that tracks drug use vulnerability and which we have modeled with repeated assessments of economic choice behavior through the first months of treatment for opioid addiction; and (2) a faster process (in the order of minutes or hours) related to the motivational state of craving that tracks immediate vulnerability and which we have modeled as a specific, gain-control like shift in the value of the object of craving. Understanding these addiction states as dynamic changes in valuation, we hope, can help identify when additional therapeutic intervention is needed on a timescale that is clinically useful as well as motivate the development of new decision- and valuation-based interventions for breaking the cycle of addiction.

Jordan Taylor
Department of Psychology and Princeton Neuroscience Institute
Princeton University

The most commonly cited human-specific cognitive abilities are generally language, abstract reasoning, and complex sociality. Our motor talents are often left off that list, as such abilities are generally not considered linked to higher cognition. Indeed, the field of sensorimotor learning often seems stuck in the subcortex, with the lens of research focused on cerebellar-driven implicit sensorimotor recalibration. This trend ignores a key element of human motor learning: rapid and flexible cognitive strategizing. Indeed, recent research from our lab, as well as others, has suggested that explicit cognitive strategies may play a bigger role than previously thought. In fact, we find that implicit learning is surprisingly inflexible — showing only small incremental changes that are insensitive to the task — which calls into question its relative importance in motor learning. Our findings suggest that much of motor learning, at least in the short-term, reflects a more complex, cognitive decision-making process which aids in the rapid, flexible selection of movements to achieve precise goals in distal regions of space. Accordingly, models of the multiple processes at work during motor learning, and hypotheses about the putative neural substrates underlying such processes, need to be broadened to accommodate the important contribution of cognitive strategies. Understanding how multiple neural systems contribute to learning should lead to the development of optimal neurorehabilitation protocols either designed to target impaired systems or bias performance to rely on systems that are relatively intact.

Sabine Kastner
Princeton Neuroscience Institute
Princeton University

The selection of information from our cluttered sensory environments is one of the most fundamental cognitive operations performed by the primate brain. In the visual domain, the selection process is thought to be mediated by a static spatial mechanism – a ‘spotlight’ that can be flexibly shifted around the visual scene. This spatial search mechanism has been associated with a large-scale network that consists of multiple nodes distributed across all major cortical lobes and includes also subcortical regions. To identify the specific functions of each network node and their functional interactions is a major goal for the field of cognitive neuroscience. In my lecture, I will challenge two common notions of attention research. First, I will show behavioral and neural evidence that the attentional spotlight is neither stationary nor unitary. In the appropriate behavioral context, even when spatial attention is sustained at a given location, additional spatial mechanisms operate flexibly in parallel to monitor the visual environment. Second, spatial attention is assumed to be under ‘top-down’ control of higher order cortex. In contrast, I will provide neural evidence indicating that attentional control is exerted through thalamo-cortical interactions. Together, this evidence indicates the need for major revisions of traditional attention accounts.

CCNP will be hosting its inaugural mini-symposium on Friday, May 5 at Rutgers University. CCNP co-directors Yael Niv and Steve Silverstein will be speaking along with CCNP investigators Nathaniel Daw and Molly Erickson. The mini-symposium coincides with a visit from NIMH Director, Joshua Gordon. Dr. Gordon will be giving the 2017 Strongwater Endowed Chair Lecture entitled “On Being a Circuit Psychiatrist”. A brief schedule is listed below. Please see the attached flyers for more information.

10:00-10:30     Steve Silverstein – “Computational modeling of low level visual processing impairments in schizophrenia”

10:30-11:00     Molly Erickson – “Computational modeling as an approach for identifying neural substrates of high-level visual abnormalities in schizophrenia”

11:00-11:30     Nathaniel Daw – “Deliberation, compulsion, and anxiety”

11:30-12:00     Yael Niv – “Tonic dopamine, response vigor and mood”

2:00-3:00        Joshua Gordon – “On Being a Circuit Psychiatrist”

CCNP Mini-Symposium
Strongwater Lecture – Joshua Gordon