Several decades of research have revealed exquisite neural selectivity in the monkey inferotemporal cortex for complex visual stimuli, including those related to social perception. The importance of these selective responses for determining perception, action, and social behavior is a challenging topic. I will present data on three novel approaches for studying the nature of inferotemporal visual representations. The first approach employs longitudinal single unit recording to study the emergence, plasticity, and stability of selective responses over time scales of weeks and months. The second approach evaluates fMRI and single-unit responses in the monkey brain during active viewing of socially rich natural videos. The third approach uses fMRI to map visual category selective responses in the ventral stream of the marmoset, with the ultimate aim of understanding the homology across primate or mammalian species. Together, these approaches aim to provide new perspectives on neural mechanisms underlying visual object and social perception in primates, including humans.
David Leopold attained a B.S. in biomedical engineering from Duke University in 1991. He subsequently received his Ph.D. from Baylor College of Medicine in 1997, where he studied neurophysiological mechanisms of multistable perception. He then did his postdoctoral work in the Logothetis lab at the Max Planck Institute for Biological Cybernetics in Tübingen, where he worked on topics related to visual perception, face recognition and fMRI. Dr. Leopold arrived at the NIH in the beginning of 2004 to establish the Section on Cognitive Neurophysiology and Imaging and to head the Neurophysiology Imaging Facility Core.]]>
Neural plasticity has many forms that express at distinct levels and serve specific functions. Recent studies indicated that, beside the classic hebbian form plasticity, neurons also utilize homeostatic mechanisms to compensate for changes in neuronal activity generated during development or through experience, for the purpose of maintaining the normal functionality. As an essential adaptive mechanism for nervous system, homeostatic plasticity is conserved through evolution, while its underlying molecular mechanism is virtually unknown. Drosophila as a model system has made valuable contributions to our general understanding of neural development and synaptic plasticity. Recently, we have demonstrated the experience-dependent homeostatic structural plasticity in fly larval visual system. This provided us opportunities to perform large-scale genetic studies and to gain a comprehensive understanding on how dendrite morphology is regulated by genetic programing and neuronal activity during development. In addition, the combination of calcium imaging and high resolution cell biological studies will provide us mechanistic insights into the homeostatic control of structural and functional synaptic plasticity.]]>
Animal behavior arises from computations in neuronal circuits, but our understanding of these computations has been frustrated by the lack of detailed synaptic connection maps, or connectomes. For example, despite intensive investigations over half a century, the neuronal implementation of local motion detection in the insect visual system remains elusive. We developed a semi-automated pipeline using electron microscopy to reconstruct a connectome, containing 379 neurons and 8,637 chemical synaptic contacts, within the Drosophila optic medulla. By matching reconstructed neurons to examples from light microscopy, we assigned neurons to cell types and assembled a connectome of the repeating module of the medulla. Within this module, we identified cell types constituting a motion detection circuit, and showed that the connections onto individual motion-sensitive neurons in this circuit were consistent with their direction selectivity. Our identification of cell types involved in motion detection allowed targeting of extremely demanding electrophysiological recordings by other labs. Preliminary results from such recordings show time delays confirming our findings. This demonstrates that connectomes can provide key insights into neuronal computations.
Dmitri “Mitya” Chklovskii is an internationally recognized inter-disciplinary scientist with contributions to neuroscience, physics, engineering, and computer science. He studied physics and engineering in St. Petersburg, Russia, then obtained a PhD in theoretical physics from MIT in 1994. After being a Junior Fellow at the Harvard Society of Fellows he switched to theoretical neuroscience and was a Sloan Fellow at the Salk Institute. In 1999, he founded a theoretical neuroscience group at Cold Spring Harbor Laboratory, where he was an Assistant and then Associate Professor. In 2007 he moved to Janelia Farm Research Campus of the Howard Hughes Medical Institute as a Group Leader. Chklovskii’s research is aimed at reverse engineering the brain by reconstructing connectomes and developing a theory of neural computation.]]>
Institute for Computational Medicine
Department of Biomedical Engineering
Johns Hopkins University
Deep brain stimulation (DBS) is clinically recognized to treat movement disorders in Parkinson’s disease (PD), but its therapeutic mechanisms remain elusive. One thing is clear though: high frequency periodic DBS (130-180Hz) is therapeutic, while low frequency DBS (i.e., less than 100Hz) is not therapeutic and may even worsen symptoms. So, what is so special about high frequency? In this talk, we address this question by discussing our viewpoint supported by recent results from our key studies of the thalamo-cortical-basal ganglia motor loop.
First, thalamic cells play a pivotal role in performing movements by selectively relaying motor-related information back to cortex under the control of modulatory signals from the basal ganglia (BG). Through computational models of the thalamic cells, bifurcation analysis, and single unit recordings from healthy primates and PD patients engaged in motor tasks, we show that (i) there is a set of BG signals (“Proper Relay Set”, PRS), under which the thalamic cells can reliably relay the motor commands, and that (ii) the BG signals belong to the PRS in healthy conditions but are outside the PRS under PD conditions.
Then, we use a detailed computational model of the motor loop under PD conditions to study the effects of DBS on the BG signals projecting to the thalamic cells. We show that high frequency periodic DBS steers the BG signals back to the PRS while lower frequency regular DBS and irregular DBS do not. Furthermore, through numerical simulation of the model and single unit recordings from healthy and PD primates, we show that DBS pulses evoke inputs that propagate through the motor loop both orthodromically (i.e., forward) and antidromically (i.e., backward) and fade away within a few milliseconds, thus having little effects on the BG signals. However, when the latency between consecutive DBS pulses is small (i.e., DBS is high frequency) and constant over time (i.e., DBS is periodic), then orthodromic and antidromic effects can overlap within the loop and result into a strong, long-lasting perturbation that ultimately drives the BG signals.
Taken together, these results provide a holistic, albeit abstract, view of motor control in healthy and PD conditions, account for the neural mechanisms of therapeutic DBS, and suggest that the merit of DBS likely depend on the closed-loop nature of the thalamo-cortical-basal ganglia system.
This study investigated why some homeless individuals seem unable to transition towards self-reliance, following traditional supportive services. It was hypothe- sized that this may be due to some cognitive dysfunction. Chronically homeless adults were compared to controls on three tests of prefrontal competency: the Iowa Gambling Task, Word Fluency (FAS), and the Burglar’s Story; they performed significantly worse than controls on all three tests. These results indicate a relationship between chronic homelessness and possible pre-frontal deficits. This may explain why some long-term homeless fail to learn from the consequences of unproductive behavior and to develop more constructive behaviors needed to attain stability.]]>
The presentation will cover 1) how positive emotions enhance our success, 2) strategies for increasing positive emotions in our lives, and 3) why positive emotions are not enough for sustained well-being.
The mechanisms of action of many therapies for nervous system indications are poorly understood. One possible explanation is that effective neurotherapeutics might have their most important effects at the circuit level rather than at the level of single channels or receptors. Without knowing how existing therapies work, how can we hope to discover new ones in a systematic manner? Fortunately, research into the function of neural circuits is poised for rapid progress, enabled by new methods to observe small and large neuronal networks in vivo, and correlate their various activities to behavior in both wild-type animals and disease models. These methods are making their way into therapeutic discovery and development just in time to re-accelerate CNS drug discovery and provide a quantum leap forward for device therapies. However, this potential will only be realized if we find reproducible ways to describe our findings to one another. I will present diverse examples of population-level investigations drawn from
my recent work: a study of state-dependent sensory encoding in the mouse barrel cortex, the use of a “medium-throughput” functional screening method to identify modulators of vesicle cycling, and a method for rapid scoring of recordings from implanted high-density electrode arrays. In each case, we started with an emerging method and developed new visualizations and reductions in order to move toward a higher-level result and make claims that are testable by others. I will try to extract common principles and discuss their implications for reproducibility and translatability of research.