Imperial College London

ProfessorSimonSchultz

Faculty of EngineeringDepartment of Bioengineering

Professor of Neurotechnology
 
 
 
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Contact

 

+44 (0)20 7594 1533s.schultz Website

 
 
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Location

 

4.11Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

75 results found

Schuck R, Quicke P, Copeland C, Garasto S, Annecchino LA, Hwang JK, Schultz SRet al., 2015, Rapid three dimensional two photon neural population scanning, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Publisher: IEEE, Pages: 5867-5870, ISSN: 1557-170X

CONFERENCE PAPER

Tolkiehn M, Schultz S, 2015, Multi-Unit Activity contains information about spatial stimulus structure in mouse primary visual cortex

This study investigates the spatial and directional tuning of Multi-Unit Activity (MUA) in mouse primary visual cortex and how MUA can reflect spatiotemporal structures contained in moving gratings. Analysis of multi-shank laminar electrophysiological recordings from mouse primary visual cortex indicates a directional preference for moving gratings around 180◦, while preferred spatial frequency peaks around 0.02 cycles per degree, which is similar as reported in single-unit studies. Using only features from MUA, we further achieved a significant performance in decoding spatial frequency or direc- tion of moving gratings, with average decoding performances of up to 58.54% for 8 directions, and 44% correctly identified spatial frequencies against chance level of 16.7%.

JOURNAL ARTICLE

Tolkiehn M, Schultz SR, 2015, Multi-Unit Activity contains information about spatial stimulus structure in mouse primary visual cortex, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Publisher: IEEE, Pages: 3771-3774, ISSN: 1557-170X

CONFERENCE PAPER

Jarvis SJ, Nikolic K, Schultz SR, 2014, Optical coactivation in cortical cells: reprogramming the excitation-inhibition balancing act to control neuronal gain in abstract and detailed models., BMC neuroscience, Vol: 15, Pages: F1-F1, ISSN: 1471-2202

JOURNAL ARTICLE

Longden KD, Muzzu T, Cook DJ, Schultz SR, Krapp HGet al., 2014, Nutritional State Modulates the Neural Processing of Visual Motion, CURRENT BIOLOGY, Vol: 24, Pages: 890-895, ISSN: 0960-9822

JOURNAL ARTICLE

Ruz ID, Schultz SR, 2014, Localising and classifying neurons from high density MEA recordings, JOURNAL OF NEUROSCIENCE METHODS, Vol: 233, Pages: 115-128, ISSN: 0165-0270

JOURNAL ARTICLE

Schuck R, Annecchino LA, Schultz SR, 2014, Scaling Up Multiphoton Neural Scanning: the SSA algorithm, Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE, Pages: 2837-2840, ISSN: 1557-170X

JOURNAL ARTICLE

Caze RD, Humphries MD, Gutkin B, Schultz SRet al., 2013, A difficult classification for neurons without dendrites, 6th International IEEE EMBS Conference on Neural Engineering (NER), Publisher: IEEE, Pages: 215-218, ISSN: 1948-3546

CONFERENCE PAPER

Grossman N, Simiaki V, Martinet C, Toumazou C, Schultz SR, Nikolic Ket al., 2013, The spatial pattern of light determines the kinetics and modulates backpropagation of optogenetic action potentials, JOURNAL OF COMPUTATIONAL NEUROSCIENCE, Vol: 34, Pages: 477-488, ISSN: 0929-5313

JOURNAL ARTICLE

Jarvis S, Nikolic K, Grossman N, Schultz SRet al., 2013, Controlling the neuronal balancing act: optical coactivation of excitation and inhibition in neuronal subdomains., Pages: P348-P348, ISSN: 1471-2202

CONFERENCE PAPER

Montani F, Phoka E, Portesi M, Schultz SRet al., 2013, Statistical modelling of higher-order correlations in pools of neural activity, PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, Vol: 392, Pages: 3066-3086, ISSN: 0378-4371

JOURNAL ARTICLE

Nikolic K, Jarvis S, Grossman N, Schultz Set al., 2013, Computational Models of Optogenetic Tools for Controlling Neural Circuits with Light, 35th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), Publisher: IEEE, Pages: 5934-5937, ISSN: 1557-170X

CONFERENCE PAPER

Onativia J, Schultz SR, Dragotti PL, 2013, A finite rate of innovation algorithm for fast and accurate spike detection from two-photon calcium imaging, JOURNAL OF NEURAL ENGINEERING, Vol: 10, ISSN: 1741-2560

JOURNAL ARTICLE

Oshiorenoya AE, Marchand P, Mutlu M, Klotz L, Schultz SRet al., 2013, Calcium Imaging In Temporal Focus, 6th International IEEE EMBS Conference on Neural Engineering (NER), Publisher: IEEE, Pages: 1525-1528, ISSN: 1948-3546

CONFERENCE PAPER

Seemungal BM, Guzman-Lopez J, Arshad Q, Schultz SR, Walsh V, Yousif Net al., 2013, Vestibular Activation Differentially Modulates Human Early Visual Cortex and V5/MT Excitability and Response Entropy, CEREBRAL CORTEX, Vol: 23, Pages: 12-+, ISSN: 1047-3211

JOURNAL ARTICLE

Caballero J, Urigueen JA, Schultz SR, Dragotti PLet al., 2012, SPIKE SORTING AT SUB-NYQUIST RATES, IEEE International Conference on Acoustics, Speech and Signal Processing, Publisher: IEEE, Pages: 585-588, ISSN: 1520-6149

CONFERENCE PAPER

Cheung K, Schultz SR, Luk W, 2012, A large-scale spiking neural network accelerator for FPGA systems, Pages: 113-120, ISSN: 0302-9743

Spiking neural networks (SNN) aim to mimic membrane potential dynamics of biological neurons. They have been used widely in neuromorphic applications and neuroscience modeling studies. We design a parallel SNN accelerator for producing large-scale cortical simulation targeting an off-the-shelf Field-Programmable Gate Array (FPGA)-based system. The accelerator parallelizes synaptic processing with run time proportional to the firing rate of the network. Using only one FPGA, this accelerator is estimated to support simulation of 64K neurons 2.5 times real-time, and achieves a spike delivery rate which is at least 1.4 times faster than a recent GPU accelerator with a benchmark toroidal network. © 2012 Springer-Verlag.

CONFERENCE PAPER

Phoka E, Wildie M, Schultz SR, Barahona Met al., 2012, Sensory experience modifies spontaneous state dynamics in a large-scale barrel cortical model, JOURNAL OF COMPUTATIONAL NEUROSCIENCE, Vol: 33, Pages: 323-339, ISSN: 0929-5313

JOURNAL ARTICLE

Saleem AB, Longden KD, Schwyn DA, Krapp HG, Schultz SRet al., 2012, Bimodal Optomotor Response to Plaids in Blowflies: Mechanisms of Component Selectivity and Evidence for Pattern Selectivity, JOURNAL OF NEUROSCIENCE, Vol: 32, Pages: 1634-1642, ISSN: 0270-6474

JOURNAL ARTICLE

Saleem AB, Longden KD, Schwyn DA, Krapp HG, Schultz SRet al., 2012, Bimodal optomotor response to plaids in blowflies: mechanisms of component selectivity and evidence for pattern selectivity., J Neurosci, Vol: 32, Pages: 1634-1642

Many animals estimate their self-motion and the movement of external objects by exploiting panoramic patterns of visual motion. To probe how visual systems process compound motion patterns, superimposed visual gratings moving in different directions, plaid stimuli, have been successfully used in vertebrates. Surprisingly, nothing is known about how visually guided insects process plaids. Here, we explored in the blowfly how the well characterized yaw optomotor reflex and the activity of identified visual interneurons depend on plaid stimuli. We show that contrary to previous expectations, the yaw optomotor reflex shows a bimodal directional tuning for certain plaid stimuli. To understand the neural correlates of this behavior, we recorded the responses of a visual interneuron supporting the reflex, the H1 cell, which was also bimodally tuned to the plaid direction. Using a computational model, we identified the essential neural processing steps required to capture the observed response properties. These processing steps have functional parallels with mechanisms found in the primate visual system, despite different biophysical implementations. By characterizing other visual neurons supporting visually guided behaviors, we found responses that ranged from being bimodally tuned to the stimulus direction (component-selective), to responses that appear to be tuned to the direction of the global pattern (pattern-selective). Our results extend the current understanding of neural mechanisms of motion processing in insects, and indicate that the fly employs a wider range of behavioral responses to multiple motion cues than previously reported.

JOURNAL ARTICLE

Schaub MT, Schultz SR, 2012, The Ising decoder: reading out the activity of large neural ensembles, JOURNAL OF COMPUTATIONAL NEUROSCIENCE, Vol: 32, Pages: 101-118, ISSN: 0929-5313

JOURNAL ARTICLE

Seemungal B, Guzman-Lopez J, Arshad Q, Schultz SR, Walsh V, Yousif Net al., 2012, VESTIBULAR ACTIVATION DIFFERENTIALLY MODULATES HUMAN EARLY VISUAL CORTEX AND V5/MT EXCITABILITY AND RESPONSE ENTROPY, Annual Meeting of the Association-of-British-Neurologists, Publisher: BMJ PUBLISHING GROUP, ISSN: 0022-3050

CONFERENCE PAPER

Cook D, Gillies D, Schultz S, 2010, Using GLMs to recover sparse connectivity in complex networks., BMC neuroscience, Vol: 11, Pages: P53-P53, ISSN: 1471-2202

JOURNAL ARTICLE

Phoka E, Wildie M, Petersen RS, Barahona M, Schultz SRet al., 2010, How is a sensory stimulus represented in ongoing dynamics in the barrel cortex?, Pages: P35-P35, ISSN: 1471-2202

CONFERENCE PAPER

Saleem AB, Chadderton P, Apergis-Schoute J, Harris KD, Schultz SRet al., 2010, Methods for predicting cortical UP and DOWN states from the phase of deep layer local field potentials, JOURNAL OF COMPUTATIONAL NEUROSCIENCE, Vol: 29, Pages: 49-62, ISSN: 0929-5313

JOURNAL ARTICLE

Cheung K, Schultz SR, Leong PHW, 2009, A parallel spiking neural network simulator, Sydney, Australia, Pages: 247-254

CONFERENCE PAPER

Schultz SR, Kitamura K, Post-Uiterweer A, Krupic J, Haeusser Met al., 2009, Spatial Pattern Coding of Sensory Information by Climbing Fiber-Evoked Calcium Signals in Networks of Neighboring Cerebellar Purkinje Cells, JOURNAL OF NEUROSCIENCE, Vol: 29, Pages: 8005-8015, ISSN: 0270-6474

JOURNAL ARTICLE

Wildie M, Luk W, Schultz SR, Leong PHW, Fidjeland AKet al., 2009, Reconfigurable acceleration of neural models with gap junctions, Pages: 439-442

We describe the design and implementation of an FPGA-based architecture for real-time simulation of spiking neural networks that include gap junctions, a type of synapse not often used in neural models due to their high computational cost. Recent research suggests that electrical synapses or gap junctions play a role in synchronizing the activity of larger groups of neurons in the brain, and are potentially important in high level functions such as cognition and memory. We suggest the simulation cost of gap junctions can be reduced by clustering them within the model, which is consistent with evidence of the structure of gap junction networks and allows each cluster to be updated in parallel. Our implementation on a Xilinx Virtex-5 FPGA demonstrates a 24.3 times speedup over a software implementation running on a cluster of four 3.6GHz Intel Xeon processors. This is part of a larger effort to construct tools capable of real-time simulation and exploration of realistic brain networks of comparable size to biological networks. © 2009 IEEE.

CONFERENCE PAPER

Saleem AB, Krapp HG, Schultz SR, 2008, Receptive field characterization by spike-triggered independent component analysis, JOURNAL OF VISION, Vol: 8, ISSN: 1534-7362

JOURNAL ARTICLE

Einarsdottir H, Montani F, Schultz SR, 2007, A mathematical model of receptive field reorganization following stroke, IEEE International Conference on Development and Learning, Pages: 211-216

CONFERENCE PAPER

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