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Dive into the research topics where Giovanni Talei Franzesi is active.

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Featured researches published by Giovanni Talei Franzesi.


Neuron | 2009

Millisecond-Timescale Optical Control of Neural Dynamics in the Nonhuman Primate Brain

Xue Han; Xiaofeng Qian; Jacob Bernstein; Huihui Zhou; Giovanni Talei Franzesi; Patrick Stern; Roderick T. Bronson; Ann M. Graybiel; Robert Desimone; Edward S. Boyden

To understand how brain states and behaviors are generated by neural circuits, it would be useful to be able to perturb precisely the activity of specific cell types and pathways in the nonhuman primate nervous system. We used lentivirus to target the light-activated cation channel channelrhodopsin-2 (ChR2) specifically to excitatory neurons of the macaque frontal cortex. Using a laser-coupled optical fiber in conjunction with a recording microelectrode, we showed that activation of excitatory neurons resulted in well-timed excitatory and suppressive influences on neocortical neural networks. ChR2 was safely expressed, and could mediate optical neuromodulation, in primate neocortex over many months. These findings highlight a methodology for investigating the causal role of specific cell types in nonhuman primate neural computation, cognition, and behavior, and open up the possibility of a new generation of ultraprecise neurological and psychiatric therapeutics via cell-type-specific optical neural control prosthetics.


Nature Methods | 2012

Automated whole-cell patch-clamp electrophysiology of neurons in vivo

Suhasa B. Kodandaramaiah; Giovanni Talei Franzesi; Brian Y. Chow; Edward S. Boyden; Craig R. Forest

Whole-cell patch-clamp electrophysiology of neurons is a gold-standard technique for high-fidelity analysis of the biophysical mechanisms of neural computation and pathology, but it requires great skill to perform. We have developed a robot that automatically performs patch clamping in vivo, algorithmically detecting cells by analyzing the temporal sequence of electrode impedance changes. We demonstrate good yield, throughput and quality of automated intracellular recording in mouse cortex and hippocampus.


The Journal of Neuroscience | 2017

Evidence for long-timescale patterns of synaptic inputs in CA1 of awake behaving mice

Ilya Kolb; Giovanni Talei Franzesi; Michael Wang; Suhasa B. Kodandaramaiah; Craig R. Forest; Edward S. Boyden; Annabelle C. Singer

Repeated sequences of neural activity are a pervasive feature of neural networks in vivo and in vitro. In the hippocampus, sequential firing of many neurons over periods of 100–300 ms reoccurs during behavior and during periods of quiescence. However, it is not known whether the hippocampus produces longer sequences of activity or whether such sequences are restricted to specific network states. Furthermore, whether long repeated patterns of activity are transmitted to single cells downstream is unclear. To answer these questions, we recorded intracellularly from hippocampal CA1 of awake, behaving male mice to examine both subthreshold activity and spiking output in single neurons. In eight of nine recordings, we discovered long (900 ms) reoccurring subthreshold fluctuations or “repeats.” Repeats generally were high-amplitude, nonoscillatory events reoccurring with 10 ms precision. Using statistical controls, we determined that repeats occurred more often than would be expected from unstructured network activity (e.g., by chance). Most spikes occurred during a repeat, and when a repeat contained a spike, the spike reoccurred with precision on the order of ≤20 ms, showing that long repeated patterns of subthreshold activity are strongly connected to spike output. Unexpectedly, we found that repeats occurred independently of classic hippocampal network states like theta oscillations or sharp-wave ripples. Together, these results reveal surprisingly long patterns of repeated activity in the hippocampal network that occur nonstochastically, are transmitted to single downstream neurons, and strongly shape their output. This suggests that the timescale of information transmission in the hippocampal network is much longer than previously thought. SIGNIFICANCE STATEMENT We found long (≥900 ms), repeated, subthreshold patterns of activity in CA1 of awake, behaving mice. These repeated patterns (“repeats”) occurred more often than expected by chance and with 10 ms precision. Most spikes occurred within repeats and reoccurred with a precision on the order of 20 ms. Surprisingly, there was no correlation between repeat occurrence and classical network states such as theta oscillations and sharp-wave ripples. These results provide strong evidence that long patterns of activity are repeated and transmitted to downstream neurons, suggesting that the hippocampus can generate longer sequences of repeated activity than previously thought.


Archive | 2011

Methods and apparatus for high-throughput neural screening

Edward S. Boyden; Jacob Bernstein; Christian T. Wentz; Giovanni Talei Franzesi; Michael V. Baratta; Brian Douglas Allen; Anthony Zorzos; Jorg Scholvin; Clifton G. Fonstad


Archive | 2010

Light-Proof Electrodes

Anthony Zorzos; Clifton G. Fonstad; Edward S. Boyden; Giovanni Talei Franzesi; August Dietrich


Journal of Neurophysiology | 2017

Mesoscale-duration activated states gate spiking in response to fast rises in membrane voltage in the awake brain

Annabelle C. Singer; Giovanni Talei Franzesi; Suhasa B. Kodandaramaiah; Francisco J. Flores; Jeremy D. Cohen; Albert K. Lee; Christoph Börgers; Craig R. Forest; Nancy Kopell; Edward S. Boyden


PMC | 2016

Assembly and operation of the autopatcher for automated intracellular neural recording in vivo

Suhasa B. Kodandaramaiah; Gregory L. Holst; Annabelle C. Singer; Giovanni Talei Franzesi; Michael L McKinnon; Craig R. Forest; Ian R. Wickersham; Edward S. Boyden


PLoS | 2012

Minimal Size of Cell Assemblies Coordinated by Gamma Oscillations

Christoph Börgers; Fiona E. N. LeBeau; Edward S. Boyden; Nancy Kopell; Giovanni Talei Franzesi

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Edward S. Boyden

Massachusetts Institute of Technology

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Craig R. Forest

Georgia Institute of Technology

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Annabelle C. Singer

Massachusetts Institute of Technology

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Anthony Zorzos

Massachusetts Institute of Technology

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Clifton G. Fonstad

Massachusetts Institute of Technology

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Jacob Bernstein

Massachusetts Institute of Technology

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Albert K. Lee

Howard Hughes Medical Institute

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