Sensimetrics Corporation

Features

The S14 insert earphones provide high-quality acoustic stimulus delivery while attenuating scanner noise. They are small enough to fit within any head coil, and can be covered with circumaural muffs for added protection if the coil allows. Replaceable Comply(TM) Canal Tips ensure sanitary conditions.

Frequency response equalization is achieved by pre-filtering stored digital stimuli. Equalization filters are provided and can be used either within Matlab or with a stand-alone filtering program (provided). A small power amplifier is required.

Model S14 System Features

High-Quality Calibrated Audio
Flat Response Over 100Hz – 8 kHz Bandwidth
Output Levels in the Ear Canal up to 110 dB SPL
Sound Attenuation from Replaceable Comply Canal Tips
Custom Digital Equalization Filters
EQ Filtering 4.0 – Software for Windows XP/Vista/7/8/10
MATLAB Functions for Loading S14 Filters

Model S14 System Includes

Binaural Earphones with 1 Meter Cables
9 Meter Cable
Small Transformer Box
Transformer Ground Cable
Custom Digital EQ Filters
EQ Filtering Software
High-Impact Carrying Case
6 pairs of Comply Foam Ear Canal Tips

FAQ

Q: Does the S14 come with a warranty?

A: The S14 earphone system comes with a one-year warranty.

Q: Is the S14 earphone system approved for use in a 3T scanner?

A: The S14 earphone system has been tested to be MR Conditional for fMRI in 3T scanners. Please see the Safety Statement.

Q: Is the S14 earphone system approved for use in a 7T or 9T scanner?

A: No. Thus far, the S14 system has been tested only in 3T scanners. Please read more about the Model S15 for earphones compatible with 7T and 9T scanners.

Q: Where can I get additional foam tips for the S14 earphones? Can I order them from Sensimetrics?

A: Sensimetrics is an authorized reseller of Comply (TM) Foam Canal Tips. You can buy them in our online store.

Q: What is the recommended method for inserting the earphones?

A: To insert each earphone, first compress the foam tip by rolling it between thumb and forefinger, narrowing its diameter. While continuing to roll it, screw it onto the post. Then quickly insert it into the ear. Hold it in the ear for about 10 seconds while the foam expands.

Q: Do you sell an fMRI-compatible active noise removal feature or attenuator with this device?

A: We do not sell any active noise reduction devices. We recommend hearing protector earmuffs on top of the S14 insert phones as an effective means of achieving added noise reduction (provided, of course, that they fit in your head coil). Search the web for ‘dielectric earmuffs’.

Q: Is there an example of the frequency response specs for the S14 earphone system?

A: Yes. Please see this example of an individual specification sheet provided with each S14 system.

Q: Is it necessary/recommended to use an amplifier? What sort of audio amplifier do I need?

A: You can generate weak signals without one, but an amplifier is needed to produce sound levels that are usually used in fMRI research. The requirements for the amplifier are very modest. The transformer/earphone combination will require no more than 3 watts per channel, which may be met by a large number of small audio amplifiers. Note that some amplifiers incorporate a loudness correction that effectively changes the frequency response along with overall gain as the volume is controlled.

The main criterion that should be met in choosing an amplifier for use with our system is that it avoids the use of any “digital,” “PCM,” “PWM,” or other high effiency topology, as they use and leak RF into the MRI environment. The chosen amplifier should be a good quality class A or class AB, (i.e., linear) unit. Additionally, although the S14 does not require high output power, we do not recommend so-called “headphone amps” as the output impedance of such amplifiers is usually far above 8 ohms. We have successfully used various amplifiers branded as “AudioSource” such as AMP100VS, AMP-100, Amp One/A, (available under various model designations and stated output powers but all of similar design). These amplifiers are available at Amazon for under $200. Similar amplifiers such as those branded “Russound” and “OSD Audio” are also suitable, as is any amplifier of linear topology, superficially indicated by the presence of a heavy power transformer instead of a lightweight switching power supply or wall adapter.

Q: I am using an analog/linear power amplifier with my S14, but I still get an artifact that goes away when the amplifier is disconnected, Do you have any suggestions?

A: Some analog amplifiers suffer from slight HF instabilities that can also introduce artifact-causing noise. Some such amplifiers can become unstable due to MRI signals accidentally coupled to the amplifier. Although this is relatively rare with modern high quality units, specific testing of the output for out-of-AF band emissions during scanning could reveal a problem. Adding additional filtering to the amplifier (input, output, power) could solve the problem, or an alternate amplifier could be part of the troubleshooting process.

Q: Do you have any official designation that the S14 earphones are MR safe?

A: The S14 is tested to be MR Conditional (according to ASTM labeling). The limits for safe use are stated in the product Safety Statement.

Q: How much attenuation of external sounds do the S14 insert earphones provide?

A: An S14 earphone inserted in a measurement device with no leaks achieves the same level of attenuation as a foam plug. Please see the Technical Note on Attenuation for more information.

Q: What type of transducer is used in the S14 earphones?

A: The earphones are piezoelectric. They contain a 12-mm disc of piezoelectric material to which a thin brass disc is bonded.

Q: What conductor material is used in the leads in the earphone cable and in the 9-meter cable?

A: The conductors are all twisted-pair copper, which is non-magnetic.

Q: How do I load the EQ filters into Matlab?

A: The filters are stored as double precision floats in a binary file. To load a filter from a file named EQF_1234L.bin, do these commands:

fid = fopen(‘EQF_1234L.bin’);
h = fread(fid, inf, ‘double’);
fclose(fid);

The filter will be in variable h.

Q: The EQ Filtering software is crashing or is not working correctly. Is there a solution?

A: Yes. The first step is to visit the download page to ensure you have the most recent version of EQ Filtering installed. (It’s Version 2.2.)

If EQ Filtering Version 2.2 still crashes or hangs, the problem may be due to incompatible headers in your .WAV files. To address this problem, try either of these two solutions:

1) Matlab. If you have Matlab you can simply read in the problematic .WAV files and write them out again, using the audioread and audiowrite commands. This process will create .WAV files with headers that are compatible with EQ Filtering.

2) SoX Sound eXchange. The second solution for .WAV files that do not work with EQ Filtering is a free utility called SoX, a command line application that reformats the header of .WAV files to ensure compatibility with EQ Filtering 2.2. The syntax is:

sox -r 44.1k inputfile.wav outputfile.wav

The “-r 44.1k” overrides the header of the input file. Be sure to set the proper sampling rate in the command line entry that matches the sampling rate of the original file. (For example, a 48K file would have the syntax:

sox -r 48k inputfile.wav outputfile.wav

Q: While installing EQ Filtering on Windows 7/8/10, I get the error “Unhandled exception has occurred in this application.” Does EQ Filtering work with 32bit and 64bit Windows 7/8/10?

A: Yes. All users are encouraged to download and install version 2.2 of the EQ Filtering software (available in 32bit and 64bit versions) from the download page.

Q: After installing EQ Filtering, I get the error “Error 1721. There is a problem with this Windows Installer package. A program required for this install to complete could not be run.” Was the installation successful?

A: Yes. Despite this error, EQ Filtering was installed successfully, and you can use the program as you would expect.

Q: What is the EQ filtering software exactly doing? Is it similar to an external/analog EQ system?

A: The EQ Filtering software uses digital filters custom-matched for your earphones to compensate for (remove) resonances in the frequency responses of the earphones. The compensation is applied to digital signals that are stored on your computer.

Q: We are seeing “zipper” and other image artifacts. Can you suggest steps for addressing this RF interference?

A: Although the majority of installations of S14 systems work with no further filtering, it is sometimes beneficial to connect the shield of the long cable to ground (using the grounding cable accessory). This is especially true when using a waveguide entrance to the scan room. If further RF filtering is necessary, insert a pair of inline low-pass filters, such as those sold by Mini-Circuits (Brooklyn NY, for example type: blp-70+) at the BNC connections of the penetration panel, (or at the BNC outputs of the transformer box in the case of waveguide-only installations). Such inline filters, having ca. -40dB at the scanner frequencies, plus grounding at the panel (or waveguide), have proven to solve RFI problems regardless of the exact cause.

Q: Our scanner room is very spacious, and the distance from the scanner to the penetration panel is longer than the 9 meter “long gray cable” that comes with S14 and S15. Do you provide extensions? Should any added extension be installed before or after the small “filter box” where the BNC leads emerge?

A: Our MRI earphone systems are designed to strike a balance between avoiding the creation of an unintentional antenna effect and minimizing deployment of an impractically large number of filters along each cable. In part, this is achieved by using the twisted pair balanced cable nearer to the scanner.

It is not recommended to try to extend the long gray cable assembly before the small square filter box where the BNC leads emerge, and doing so will void the warranty. Additionally, each installation may have unique characteristics that prevent fine tuning from being a one-size-fits-all prospect. The ultimate fine tuning must be done by the engineer or technician in charge of the site.

With that in mind, we have had success with a relatively simple solution that is worth trying if you find yourself needing more length to reach the panel or waveguide. Purchase 50 ohm rg-58 patch cables of the desired length (be sure they are of highest quality and contain good percentage of shielding coverage, and a combination of braid and foil as the shield). Make note of the required gender at each end (the BNC’s on our product are male and thus plug into female, the penetration panel is almost universally female thus requiring a male on that side of the extension. If you use extension patch cables with males on both ends you will need to purchase gender changers, as well, to mate male to male on one end of long gray cable).

Even the best of coax extension cables are not ideally shielded especially in terms of any osciallating magnetic field that may be present at the far end of the scan room. We recommend inserting inline low pass filters such as the blp-70-75+ low pass filter from MiniCircuits (or any filters that pass audio frequencies but have a lossy stoppand effective around the larmor frequency of the scanner) in various places as needed.

For example, one might deploy three (times two for stereo) along each extension: at the start, at the end, and if you span the extension distance using two cables for each channel instead of in one single span, you will be able to also put one in the middle of the extension. This is almost a worst case scenario, as often the filtering that already exists in the transformer box at the panel end, and the filter in the small box at the end of the “long gray wire”, provide enough attenuation.

This is especially true for the S15 product, which includes improved filtering over that of the S14 product. It is preferable to assemble these connectors, cables, filters, outside of the scan room as the connector hardware may exhibit some attraction to the bore. Bring the assembled extension cable into the room close to the penetration panel and affix it there by immediately plugging in the BNCs. In this way you will not be tempted to make a mistake such as placing the hardware on the patient bed.

Documentation

Please consult the following documents for important information about Model S14 Insert Earphones for fMRI Research:

S14 Instructions (PDF)

EQ Filtering Program Instructions (PDF)

MRI Insert Earphones – Technical Note on Attenuation (PDF)

Sample Frequency Response (PDF)

S14 fMRI Safety Information (PDF)

S14 Wiring Diagram (PDF)

Accessories

Replaceable Comply (TM) Foam Canal Tips – $325

Sensimetrics is an authorized reseller of Comply (TM) Foam Canal Tips.

Sensimetrics’ Model S14 was tested for safety using Comply’s military-grade canal tips. The tips conform to the ear canal to maintain an acoustic seal, deliver maximum noise reduction, and ensure sanitary conditions.

For more detailed specifications of Comply (TM) Foam Canal Tips, visit Comply’s product website.

S14 BNC Penetration Panel Adaptor Cables

BNC Penetration Panel Adaptor Cables – $300

Allows “differential pass-through” of the headphone signal coming from the transformer box when used with grounded penetration panels. Converts the normal “single BNC per channel” connections to “two BNCs per channel” (thus stereo requires 4 BNC positions on each side of the panel). This optional configuration allows the user to maintain the balanced drive signal from the transformer. While this accessory is not usually needed, it may be helpful in certain situations when tracking down RF leakage or artifacts peculiar to a particular installation.

Shield Cable – $10

This accessory (formerly called the ‘Choke Grounding Cable’) enables a direct connection from the shield conductor of the long cable assembly to a user specified ground at the penetration panel. Such connection is not generally used, but it may be helpful in certain situations when tracking down RF leakage or artifacts peculiar to a particular installation.

Studies

Published studies using Sensimetrics insert earphones for fMRI research:

Processing pathways for emotional vocalizations
Tiffany Grisendi, Olivier Reynaud, Stephanie Clarke, Sandra Da Costa
Brain Structure and Function – July 6, 2019, pp 1–18
https://doi.org/10.1007/s00429-019-01912-x

Language learning experience and mastering the challenges of perceiving speech in noise
Shanna Kousaie, Shari Baumb, Natalie A. Phillips, Vincent Gracco, Debra Titon, Jen-Kai Chen, Xiaoqian J. Chai, Denise Klein
Brain and Language – Volume 196, September 2019, 104645
https://doi.org/10.1016/j.bandl.2019.104645

Divergence in the functional organization of human and macaque auditory cortex revealed by fMRI responses to harmonic tones
Sam V. Norman-Haignere, Nancy Kanwisher, Josh H. McDermott, Bevil R. Conway
Nature Neuroscience – Volume 22, pages 1057–1060, June 10, 2019
https://doi.org/10.1038/s41593-019-0410-7

Early Blindness Shapes Cortical Representations of Auditory Frequency within Auditory Cortex
Elizabeth Huber, Kelly Chang, Ivan Alvarez, Aaron Hundle, Holly Bridge, Ione Fine
Journal of Neuroscience – Vol. 39, Issue 26, 26 Jun 2019
https://doi.org/10.1523/JNEUROSCI.2896-18.2019

Processing complexity increases in superficial layers of human primary auditory cortex
Michelle Moerel, Federico De Martino, Kâmil Uğurbil, Essa Yacoub, Elia Formisano
Nature – Scientific Reports – Volume 9, Article number: 5502 (2019)
https://doi.org/10.1038/s41598-019-41965-w

Brain activity during reciprocal social interaction investigated using conversational robots as control condition
Birgit Rauchbauer, Bruno Nazarian, Morgane Bourhis, Magalie Ochs, Laurent Prévot, Thierry Chaminade
The Royal Society – March 11, 2019, Volume 374, Issue 1771
https://doi.org/10.1098/rstb.2018.0033

Musical reward prediction errors engage the nucleus accumbens and motivate learning
Benjamin P. Gold, Ernest Mas-Herrero, Yashar Zeighami, Mitchel Benovoy, Alain Dagher, Robert J. Zatorre
PNAS February 19, 2019 116 (8) 3310-3315
https://doi.org/10.1073/pnas.1809855116

Separable neural representations of sound sources: Speaker identity and musical timbre
Mattson Ogg, Dustin Moraczewski, Stefanie E. Kuchinsky, L. Robert Slevc
NeuroImage – Volume 191, 1 May 2019, Pages 116-126
https://doi.org/10.1016/j.neuroimage.2019.01.075

Partially Overlapping Brain Networks for Singing and Cello Playing
Melanie Segado, Avrum Hollinger, Joseph Thibodeau, Virginia Penhune, Robert J. Zatorre
Frontiers in Neuroscience, 28 May 2018
https://doi.org/10.3389/fnins.2018.00351

Functionally distinct language and Theory of Mind networks are synchronized at rest and during language comprehension
Alexander M. Paunov, Idan A. Blank, Evelina Fedorenko
Journal of Neurophysiology – March 29, 2019
https://doi.org/10.1152/jn.00619.2018

The impact of spelling regularity on handwriting production: A coupled fMRI and kinematics study
Sarah Palmis, Jean-LucVelay, Elie Fabiani, Bruno Nazarian, Jean-Luc Anton, Michel Habib, Sonia Kandel, Marieke Longcamp
Cortex – Volume 113, April 2019, Pages 111-127
https://doi.org/10.1016/j.cortex.2018.11.024

Young children’s neural processing of their mother’s voice: An fMRI study
Pan Liu, Pamela M. Cole, Rick O. Gilmore, Koraly E. Pérez-Edgar, Michelle C. Vigeant, Peter Moriarty, K. Suzanne Scherfa
Neuropsychologia – Volume 122, January 2019, Pages 11-19
https://doi.org/10.1016/j.neuropsychologia.2018.12.003

Hierarchy of speech-driven spectrotemporal receptive fields in human auditory cortex
Jonathan H. Venezia, Steven M. Thurman, Virginia M. Richards, Gregory Hickok
NeuroImage – Volume 186, 1 February 2019, Pages 647-666
https://doi.org/10.1016/j.neuroimage.2018.11.049

Interaction of the effects associated with auditory-motor integration and attention-engaging listening tasks
Patrik Wikman, Teemu Rinne
Social Cognitive and Affective Neuroscience, Volume 13, Issue 12, December 2018, Pages 1293–1304
https://doi.org/10.1016/j.neuropsychologia.2018.11.006

A drama movie activates brains of holistic and analytical thinkers differentially
Mareike Bacha-Trams, Yuri I Alexandrov, Emilia Broman, Enrico Glerean, Minna Kauppila, Janne Kauttonen, Elisa Ryyppö, Mikko Sams, Iiro P Jääskeläinen
Social Cognitive and Affective Neuroscience, Volume 13, Issue 12, December 2018, Pages 1293–1304
https://doi.org/10.1093/scan/nsy099

Reduced auditory cortical adaptation in autism spectrum disorder
Rachel Millin, Tamar Kolodny, Anastasia V Flevaris, Alexander M Kale, Michael-Paul Schallmo, Jennifer Gerdts, Raphael A Bernier, Scott Murray
eLife Sciences – 26 October 2018
https://doi.org/10.7554/eLife.36493

Feature-dependent intrinsic functional connectivity across cortical depths in the human auditory cortex
Pu-Yeh Wu, Ying-Hua Chu, Jo-Fu Lotus Lin, Wen-Jui Kuo, Fa-Hsuan Lin
Nature: Scientific Reports – Volume 8, Article number: 13287 September 5, 2018
https://doi.org/10.1038/s41598-018-31292-x

Reduced sound-evoked and resting-state BOLD fMRI connectivity in tinnitus
Benedikt Hofmeier, Stephan Wolpert, Ebrahim Saad Aldamer, Moritz Walter, John Thiericke, Christoph Braun, Dennis Zelle, Lukas Rüttiger, Uwe Klose, Marlies Knipper
NeuroImage: Clinical – Volume 20, 2018, Pages 637-649
https://doi.org/10.1016/j.nicl.2018.08.029

Active Sound Localization Sharpens Spatial Tuning in Human Primary Auditory Cortex
Kiki van der Heijden, Josef P. Rauschecker, Elia Formisano, Giancarlo Valente, Beatrice de Gelder
Journal of Neuroscience – 3 October 2018, 38 (40) 8574-8587
https://doi.org/10.1523/JNEUROSCI.0587-18.2018

Singing in the brain: Neural representation of music and voice as revealed by fMRI
Jocelyne C. Whitehead, Jorge L. Armony
Human Brain Mapping – Volume39, Issue12 – December 2018, Pages 4913-4924
https://doi.org/10.1002/hbm.24333

Functional connectivity within the voice perception network and its behavioural relevance
Virginia Aglieri, Thierry Chaminade, Sylvain Takerkart, Pascal Belin
NeuroImage – Volume 183, December 2018, Pages 356-365
https://doi.org/10.1016/j.neuroimage.2018.08.011

Free viewing of talking faces reveals mouth and eye preferring regions of the human superior temporal sulcus
Johannes Rennig, Michael S. Beauchamp
NeuroImage – Volume 183, December 2018, Pages 25-36
https://doi.org/10.1016/j.neuroimage.2018.08.008

Listening for memories: Attentional focus dissociates functional brain networks engaged by memory-evoking music
Benjamin Kubit, Petr Janata
Psychomusicology: Music, Mind, and Brain, 28(2), 82-100
http://dx.doi.org/10.1037/pmu0000210

Neural specialization of phonological and semantic processing in young children
Yael Weiss, Hannah G. Cweigenberg, James R. Booth
Human Brain Mapping – June 28, 2018
https://doi.org/10.1002/hbm.24274

Hearing and orally mimicking different acoustic-semantic categories of natural sound engage distinct left hemisphere cortical regions
James W. Lewis, Magenta J. Silberman, Jeremy J. Donai, Chris A. Frum, Julie A. Brefczynski-Lewis
Brain and Language – Volume 183, August 2018, Pages 64-78
https://doi.org/10.1016/j.bandl.2018.05.002

Neural Prediction Errors Distinguish Perception and Misperception of Speech
Helen Blank, Marlene Spangenberg, Matthew H. Davis
Journal of Neuroscience – 4 July 2018, 38 (27) 6076-6089
https://doi.org/10.1523/JNEUROSCI.3258-17.2018

Neural network retuning and neural predictors of learning success associated with cello training
Indiana Wollman, Virginia Penhune, Melanie Segado, Thibaut Carpentier, Robert J. Zatorre
PNAS – June 26, 2018 115 (26) E6056-E6064
https://doi.org/10.1073/pnas.1721414115

Neural representation of vowel formants in tonotopic auditory cortex
Julia M. Fisher, Frederic K. Dick, Deborah F. Levy, Stephen M. Wilson
Annals of The New York Academy of Sciences – May 9, 2018
https://doi.org/10.1016/j.neuroimage.2018.05.072

Cross‐classification of musical and vocal emotions in the auditory cortex
Sébastien Paquette, Sylvain Takerkart, Shinji Saget, Isabelle Peretz, Pascal Belin
Annals of The New York Academy of Sciences – May 9, 2018
https://doi.org/10.1111/nyas.13666

Exploring collective experience in watching dance through intersubject correlation and functional connectivity of fMRI brain activity
Frank E. Pollick, Staci Vicary, Katie Noble, Naree Kim, Seonhee Jang, Catherine J. Stevens
Progress in Brain Research – Volume 237, 2018, Pages 373-397
https://doi.org/10.1016/bs.pbr.2018.03.016

A Task-Optimized Neural Network Replicates Human Auditory Behavior, Predicts Brain Responses, and Reveals a Cortical Processing Hierarchy
Alexander J.E. Kell, Daniel L.K. Yamins, Erica N. Shook, Sam V. Norman-Haignere, Josh H. McDermott
Neuron – Volume 98, Issue 3, 2 May 2018, Pages 630-644.e16
https://doi.org/10.1016/j.neuron.2018.03.044

Distributed affective space represents multiple emotion categories across the human brain
Heini Saarimaki, Lara Farzaneh Ejtehadian, Enrico Glerean, Iiro P. Jaaskelainen, Patrik Vuilleumier, Mikko Sams, Lauri Nummenmaa
Social Cognitive and Affective Neuroscience, 2018, 471–482
https://doi.org/10.1093/scan/nsy018

Incongruent pitch cues are associated with increased activation and functional connectivity in the frontal areas
Jo-Fu Lotus Lin, Toshiaki Imada, Patricia K. Kuhl, Fa-Hsuan Lin
Nature Scientific Reports Volume 8, Article number: 5206 (2018)
https://doi.org/10.1038/s41598-018-23287-5

Sensorimotor Representation of Speech Perception – Cross-Decoding of Place of Articulation Features during Selective Attention to Syllables in 7T fMRI
Mario E. Archila-Meléndez, Giancarlo Valente, Joao Correia, Rob P. W. Rouhl, Vivianne H. van Kranen-Mastenbroek, Bernadette M. Jansma
eNeuro – March 22, 2018
https://doi.org/10.1523/ENEURO.0252-17.2018

Frequency-specific attentional modulation in human primary auditory cortex and midbrain
Lars Riecke, Judith C. Peters, Giancarlo Valente, Benedikt A. Poser, Valentin G. Kemper, Elia Formisano, Bettina Sorger
NeuroImage – Volume 174, 1 July 2018, Pages 274-287
https://doi.org/10.1016/j.neuroimage.2018.03.038

Acoustic and higher-level representations of naturalistic auditory scenes in human auditory and frontal cortex
Lars Hausfeld, Lars Riecke, Elia Formisano
NeuroImage – Volume 173, June 2018, Pages 472-483
https://doi.org/10.1016/j.neuroimage.2018.02.065

Inter-subject synchrony as an index of functional specialization in early childhood
Dustin Moraczewski, Gang Chen, Elizabeth Redcay
Nature – Scientific Reports Volume 8, Article number: 2252 (2018)
https://doi.org/10.1038/s41598-018-20600-0

Decoding auditory spatial and emotional information encoding using multivariate versus univariate techniques
James H. Kryklywy, Ewan A. Macpherson, Derek G. V. Mitchell
Experimental Brain Research – April 2018, Volume 236, Issue 4, pp 945–953
https://doi.org/10.1007/s00221-018-5185-7

Intrinsic, stimulus-driven and task-dependent connectivity in human auditory cortex
Suvi Häkkinen, Teemu Rinne
Brain Structure and Function – June 2018, Volume 223, Issue 5, pp 2113–2127
https://doi.org/10.1007/s00429-018-1612-6

Phase Entrainment of Brain Oscillations Causally Modulates Neural Responses to Intelligible Speech
Benedikt Zoefel, Alan Archer-Boyd, Matthew H. Davis
Current Biology – Volume 28, Issue 3, 5 February 2018, Pages 401-408.e5
https://doi.org/10.1016/j.cub.2017.11.071

Convergence of spoken and written language processing in the superior temporal sulcus
Stephen M. Wilson, Alexa Bautist, Angelica McCarron
NeuroImage – Volume 171, 1 May 2018, Pages 62-74
https://doi.org/10.1016/j.neuroimage.2017.12.068

Musical training sharpens and bonds ears and tongue to hear speech better
Yi Du, Robert J. Zatorre
PNAS – December 19, 2017 114 (51) 13579-13584
https://doi.org/10.1073/pnas.1712223114

Cortical networks for auditory detection with and without informational masking: Task effects and implications for conscious perception
Katrin Wiegand, Sabine Heiland, Christian H. Uhlig, Andrew R. Dykstra, Alexander Gutschalk
NeuroImage – Volume 167, 15 February 2018, Pages 178-190
https://doi.org/10.1016/j.neuroimage.2017.11.036

Reconstructing Tone Sequences from Functional Magnetic Resonance Imaging Blood-Oxygen Level Dependent Responses within Human Primary Auditory Cortex
Kelly H. Chang, Jessica M. Thomas, Geoffrey M. Boynton, Ione Fine
Frontiers In Psychology, 14 November 2017
https://doi.org/10.3389/fpsyg.2017.01983

Development of the Visual Word Form Area Requires Visual Experience: Evidence from Blind Braille Readers
Judy S. Kim, Shipra Kanjlia, Lotfi B. Merabet, Marina Bedny
Journal of Neuroscience 22 November 2017, 37 (47) 11495-11504
https://doi.org/10.1523/JNEUROSCI.0997-17.2017

Auditory Frequency Representations in Human Somatosensory Cortex
Alexis Pérez-Bellido, Kelly Anne Barnes, Lexi E Crommett, Jeffrey M Yau
Cerebral Cortex – Volume 28, Issue 11, November 2018, Pages 3908–3921
https://doi.org/10.1093/cercor/bhx255

Exploring the neural substrates of misinformation processing
Andrew Gordon, Jonathan C. W. Brooks, Susanne Quadflieg, Ullrich K.H. Ecker, Stephan Lewandowsky
Neuropsychologia – Volume 106, November 2017, Pages 216-224
https://doi.org/10.1016/j.neuropsychologia.2017.10.003

Reduced Laughter Contagion in Boys at Risk for Psychopathy
Elizabeth O’Nions, César F.Lima, Sophie K.Scott, Ruth Roberts, Eamon J. McCrory, Essi Viding
Current Biology – Volume 27, Issue 19, 9 October 2017, Pages 3049-3055.e4
https://doi.org/10.1016/j.cub.2017.08.062

High spatio‐temporal resolution in functional MRI with 3D echo planar imaging using cylindrical excitation and a CAIPIRINHA undersampling pattern
Wietske van der Zwaag, Olivier Reynaud, Mayur Narsude, Daniel Gallichan, José P. Marques
Magnetic Resonance In Medicine – September 14, 2017
https://doi.org/10.1002/mrm.26906

Cannabis Dampens the Effects of Music in Brain Regions Sensitive to Reward and Emotion
Tom P Freeman, Rebecca A Pope, Matthew B Wall, James A Bisby, Maartje Luijten, Chandni Hindocha, Claire Mokrysz, Will Lawn, Abigail Moss, Michael A P Bloomfield, Celia J A Morgan, David J Nutt, H Valerie Curran
International Journal of Neuropsychopharmacology, Volume 21, Issue 1, January 2018, Pages 21–32
https://doi.org/10.1093/ijnp/pyx082

Auditory Statistical Learning During Concurrent Physical Exercise and the Tolerance for Pitch, Tempo, and Rhythm Changes
Tatsuya Daikoku, Yuji Takahashi, Nagayoshi Tarumoto, Hideki Yasuda
Human Kinetics – Volume: 22 Issue: 3 Pages: 233-244
https://doi.org/10.1123/mc.2017-0006

Evidence for cue-independent spatial representation in the human auditory cortex during active listening
Nathan C. Higgins, Susan A. McLaughlin, Teemu Rinne, and G. Christopher Stecker
PNAS – August 21, 2017
https://doi.org/10.1073/pnas.1707522114

Amplification of local changes along the timescale processing hierarchy
Yaara Yeshurun, Mai Nguyen, and Uri Hasson
PNAS – August 15, 2017
https://doi.org/10.1073/pnas.1701652114

Sensory-Biased and Multiple-Demand Processing in Human Lateral Frontal Cortex
Abigail L. Noyce, Nishmar Cestero, Samantha W. Michalka, Barbara G. Shinn-Cunningham and David C. Somers
Journal of Neuroscience – September 6, 2017, 37 (36) 8755-8766
https://doi.org/10.1523/JNEUROSCI.0660-17.2017

Predictive processing increases intelligibility of acoustically distorted speech: Behavioral and neural correlates
Maria Hakonen, Patrick J. C. May, Iiro P. Jääskeläinen, Emma Jokinen, Mikko Sams, Hannu Tiitinen
Brain and Behavior – August 4, 2017
https://doi.org/10.1002/brb3.789

Subcortical and cortical correlates of pitch discrimination: Evidence for two levels of neuroplasticity in musicians
Federica Bianchi, Jens Hjortkjær, Sébastien Santurette, Robert J. Zatorre, Hartwig R. Siebner, Torsten Daua
NeuroImage – Volume 163, December 2017, Pages 398-412
https://doi.org/10.1016/j.neuroimage.2017.07.057

Functional brain outcomes of L2 speech learning emerge during sensorimotor transformation
Daniel Carey, Marc E. Miquel, Bronwen G. Evans, Patti Adank, Carolyn McGettigan
NeuroImage – Volume 159, 1 October 2017, Pages 18-31
https://doi.org/10.1016/j.neuroimage.2017.06.053

It doesn’t matter what you say: FMRI correlates of voice learning and recognition independent of speech content
Romi Zäske, Bashar Awwad Shiekh Hasan, Pascal Belin
Cortex – Volume 94, September 2017, Pages 100-112
https://doi.org/10.1016/j.cortex.2017.06.005

Adult-like processing of naturalistic sounds in auditory cortex by 3- and 9-month old infants
Conor J.Wild, Annika C. Linke, Leire Zubiaurre-Elorza, Charlotte Herzmann, Hester Duffy, Victor K. Han, David S.C. Lee, Rhodri Cusack
NeuroImage – Volume 157, 15 August 2017, Pages 623-634
https://doi.org/10.1016/j.neuroimage.2017.06.038

Cingulo-opercular activity affects incidental memory encoding for speech in noise
Kenneth I. Vaden Jr., Susan Teubner-Rhodes, Jayne B. Ahlstrom, Judy R. Dubno, Mark, A. Eckert
NeuroImage – Volume 157, 15 August 2017, Pages 381-387
https://doi.org/10.1016/j.neuroimage.2017.06.028

The Hierarchical Cortical Organization of Human Speech Processings
Wendy A. de Heer, Alexander G. Huth, Thomas L. Griffiths, Jack L. Gallant and Frédéric E. Theunissen
Journal of Neuroscience – July 5,2017
https://doi.org/10.1523/JNEUROSCI.3267-16.2017

Reconstructing the spectrotemporal modulations of real-life sounds from fMRI response patterns
Roberta Santoro, Michelle Moerel, Federico De Martino, Giancarlo Valente, Kamil Ugurbil, Essa Yacoub, and Elia Formisano
PNAS – April 18, 2017
https://doi.org/10.1073/pnas.1617622114

You talkin’ to me? Communicative talker gaze activates left-lateralized superior temporal cortex during perception of degraded speech
Carolyn McGettigan, Kyle Jasmin, Frank Eisner, Zarinah K. Agnew, Oliver J. Josephs, Andrew J. Calder, Rosemary Jessop, Rebecca P. Lawson, Mona Spielmann, Sophie K. Scottb
Neuropsychologia – Volume 100, June 2017, Pages 51-63
https://doi.org/10.1016/j.neuropsychologia.2017.04.013

Sensitivity and specificity considerations for fMRI encoding, decoding, and mapping of auditory cortex at ultra-high field
Michelle Moerel, Federico De Martino, Valentin G. Kemper, Sebastian Schmitter, An T. Vu, Kâmil Uğurbil, Elia Formisano, Essa Yacoub
NeuroImage – Volume 164, 1 January 2018, Pages 18-31
https://doi.org/10.1016/j.neuroimage.2017.03.063

Brain activity associated with selective attention, divided attention and distraction
Emma Salo, Viljami Salmela, Juha Salmi, Jussi Numminen, Kimmo Alho
Brain Research – Volume 1664, 1 June 2017, Pages 25-36
https://doi.org/10.1016/j.brainres.2017.03.021

The left intraparietal sulcus adapts to symbolic number in both the visual and auditory modalities: Evidence from fMRI
Stephan E. Vogel, Celia Goffin, Joshua Bohnenberger, Karl Koschutnig, Gernot Reishofer, Roland H. Grabner, Daniel Ansari
NeuroImage – Volume 153, June 2017, Pages 16-27
https://doi.org/10.1016/j.neuroimage.2017.03.048

Transient human auditory cortex activation during volitional attention shifting
Christian Harm Uhlig, Alexander Gutschalk
PLoS ONE – March 8, 2017
https://doi.org/10.1371/journal.pone.0172907

An fMRI study of implicit language learning in developmental language impairment
Elena Plante, Dianne Patterson, Michelle Sandoval, Christopher J. Vance, Arve E. Asbjørnsen
NeuroImage: Clinical – Volume 14, 2017, Pages 277-285
https://doi.org/10.1016/j.nicl.2017.01.027

Same Story, Different Story: The Neural Representation of Interpretive Frameworks
Yaara Yeshurun, Stephen Swanson, Erez Simony, Janice Chen, Christina Lazaridi, Christopher J. Honey, Uri Hasson
Association of Psychological Science – Volume 28 Issue 3, March 2017
https://doi.org/10.1177/0956797616682029

Functional and Quantitative MRI Mapping of Somatomotor Representations of Human Supralaryngeal Vocal Tract
Daniel Carey, Saloni Krishnan, Martina F. Callaghan, Martin I. Sereno, Frederic Dick
Cerebral Cortex – Volume 27, Issue 1, January 2017, Pages 265–278
https://doi.org/10.1093/cercor/bhw393

Who’s that Knocking at My Door? Neural Bases of Sound Source Identification
Guillaume Lemaitre, John A Pyles, Andrea R Halpern, Nicole Navolio, Matthew Lehet, Laurie M Heller
Cerebral Cortex – Volume 28, Issue 3, March 2018, Pages 805–818
https://doi.org/10.1093/cercor/bhw397

Representations of Pitch and Timbre Variation in Human Auditory Cortex
Emily J. Allen, Philip C. Burton, Cheryl A. Olman, Andrew J. Oxenham
The Journal of Neuroscience – 1 February 2017, 37 (5) 1284-1293
https://doi.org/10.1523/JNEUROSCI.2336-16.2016

Auditory biological marker of concussion in children
Nina Kraus, Elaine C. Thompson, Jennifer Krizman, Katherine Cook, Travis White-Schwoch, Cynthia R. LaBella
Nature.com – Scientific Reports – Article number: 39009 (2016)
https://doi.org/10.1038/srep39009

Prediction Errors but Not Sharpened Signals Simulate Multivoxel fMRI Patterns during Speech Perception
Helen Blank, Matthew H. Davis
PLOS – November 15, 2016
https://doi.org/10.1371/journal.pbio.1002577

Gaming is related to enhanced working memory performance and task-related cortical activity
M. Moisala, V. Salmela, L. Hietajärvi, S. Carlson, V. Vuontela, K. Lonka, K. Hakkarainen, K. Salmela-Aro, K. Alho
Brain Research – Volume 1655, 15 January 2017, Pages 204-215
https://doi.org/10.1016/j.brainres.2016.10.027

Tonotopic maps in human auditory cortex using arterial spin labeling
Anna Gardumi, Dimo Ivanov, Martin Havlicek, Elia Formisano, Kâmil Uludağ
Human Brain Mapping – Volume38 , Issue3, March 2017, Pages 1140-1154
https://doi.org/10.1002/hbm.23444

Learning and retrieving holistic and componential visual-verbal associations in reading and object naming
Connor Quinn, J.S.H. Taylor, Matthew H. Davis
Neuropsychologia – Volume 98, April 2017, Pages 68-84
https://doi.org/10.1016/j.neuropsychologia.2016.09.025

Intracortical depth analyses of frequency-sensitive regions of human auditory cortex using 7T fMRI
Jyrki Ahveninen, Wei-Tang Chang, Samantha Huang, Boris Keil, Norbert Kopco, Stephanie Rossi, Giorgio Bonmassar, Thomas Witzel, Jonathan R. Polimeni
NeuroImage – Volume 143, December 2016, Pages 116-127
https://doi.org/10.1016/j.neuroimage.2016.09.010

Functional activity and white matter microstructure reveal the independent effects of age of acquisition and proficiency on second-language learning
Emily S. Nichols, Marc F. Joanisse
NeuroImage – Volume 143, December 2016, Pages 15–25
doi: 10.1016/j.neuroimage.2016.08.053

Brain bases of morphological processing in Chinese-English bilingual children
Ka I Ip, Lucy Shih-Ju Hsu, Maria M. Arredondo, Twila Tardif, Ioulia Kovelman
Developmental Science – 14 August 2016
doi: 10.1111/desc.12449

Whispering – The hidden side of auditory communication
Sascha Frühholz, Wiebke Trost, Didier Grandjean
NeuroImage – Available online 12 August 2016
doi: 10.1016/j.neuroimage.2016.08.023

Dynamic reconfiguration of the default mode network during narrative comprehension
Erez Simony, Christopher J Honey, Janice Chen, Olga Lositsky, Yaara Yeshurun, Ami Wiesel, Uri Hasson
Nature Communications – Article number: 12141, 18 July 2016
doi: 10.1038/ncomms12141

Somatosensory attention identifies both overt and covert awareness in disorders of consciousness
Raechelle M. Gibson B.Sc, Srivas Chennu PhD, Davinia Fernández-Espejo PhD, Lorina Naci PhD, Adrian M. Owen PhD, Damian Cruse PhD
Annals of Neurology – 4 August 2016
doi: 10.1002/ana.24726

Mapping the cortical representation of speech sounds in a syllable repetition task
Christopher J. Markiewicz, Jason W. Bohland
NeuroImage – Volume 141, 1 November 2016, Pages 174–190
doi: 10.1016/j.neuroimage.2016.07.023

A new fun and robust version of an fMRI localizer for the frontotemporal language system
Terri L. Scott, Jeanne Gallée, Evelina Fedorenko
Cognitive Neuroscience – Page 1-10 | Received 02 Mar 2016, Published online: 07 Jul 2016
doi: 10.1080/17588928.2016.1201466

The representation of level and loudness in the central auditory system for unilateral stimulation
Oliver Behler, Stefan Uppenkamp
NeuroImage – Volume 139, 1 October 2016, Pages 176–188
doi: 10.1016/j.neuroimage.2016.06.025

Velocity Selective Networks in Human Cortex Reveal Two Functionally Distinct Auditory Motion Systems
Jhao-An Meng, Kourosh Saberi, I-Hui Hsieh
PLOS One – June 13, 2016
doi: 10.1371/journal.pone.0157131

Neural Processing of Emotional Musical and Nonmusical Stimuli in Depression
Rebecca J. Lepping, Ruth Ann Atchley, Evangelia Chrysikou, Laura E. Martin, Alicia A. Clair, Rick E. Ingram, W. Kyle Simmons, Cary R. Savage
PLOS One – June 10, 2016
doi: 10.1371/journal.pone.0156859

Natural speech reveals the semantic maps that tile human cerebral cortex
Alexander G. Huth, Wendy A. de Heer, Thomas L. Griffiths, Frédéric E. Theunissen, Jack L. Gallant
Nature – Volume 532, 28 April 2016, 453–458
doi: 10.1038/nature17637

A Brain System for Auditory Working Memory
Sukhbinder Kumar, Sabine Joseph, Phillip E. Gander, Nicolas Barascud, Andrea R. Halpern, Timothy D. Griffiths
The Journal of Neuroscience, 20 April 2016, 36(16): 4492-4505
doi: 10.1523/JNEUROSCI.4341-14.2016

Auditory fMRI of Sound Intensity and Loudness for Unilateral Stimulation
Oliver Behler, Stefan Uppenkamp
Advances in Experimental Medicine and Biology – Volume 894, 15 April 2016, Pages 165-174
doi: 10.1007/978-3-319-25474-6_18

Media multitasking is associated with distractibility and increased prefrontal activity in adolescents and young adults
M. Moisala, V. Salmela, L. Hietajärvi, E. Salo, S. Carlson, O. Salonen, K. Lonka, K. Hakkarainen, K. Salmela-Aro, K. Alho
NeuroImage – Volume 134, 1 July 2016, Pages 113–121
doi: 10.1016/j.neuroimage.2016.04.011

Validity and reliability of four language mapping paradigms
Stephen M. Wilson, Alexa Bautista, Melodie Yen, Stefanie Lauderdale, Dana K. Eriksson
NeuroImage: Clinical – Available Online March 24, 2016
doi: 10.1016/j.nicl.2016.03.015

Functional magnetic resonance imaging confirms forward suppression for rapidly alternating sounds in human auditory cortex but not in the inferior colliculus
Christian Harm Uhlig, Andrew R. Dykstra, Alexander Gutschalk
Hearing Research – Volume 335, May 2016, Pages 25–32
doi: 10.1016/j.heares.2016.02.010

The effect of spatial resolution on decoding accuracy in fMRI multivariate pattern analysis
Anna Gardumi, Dimo Ivanov, Lars Hausfeld, Giancarlo Valente, Elia Formisano, Kâmil Uludağ
NeuroImage – Volume 132, 15 May 2016, Pages 32–42
doi: 10.1016/j.neuroimage.2016.02.033

Auditory functional magnetic resonance imaging in dogs – normalization and group analysis and the processing of pitch in the canine auditory pathways
Jan-Peter Bach, Matthias Lüpke, Peter Dziallas, Patrick Wefstaedt, Stefan Uppenkamp, Hermann Seifert, Ingo Nolte
BMC Veterinary Research – December 2016
doi: 10.1186/s12917-016-0660-5

In young readers, the left hemisphere supports the link between temporal processing and phonological awareness
Margaret Ugolini, Neelima Wagley, Ka Ip, Lucy Shih-Ju Hsu, Maria M. Arredondo & Ioulia Kovelman
Speech, Language and Hearing – Published online: February 16, 2016
doi: 10.1080/2050571X.2015.1101894

Distortion products in auditory fMRI research: Measurements and solutions
Sam Norman-Haignere, Josh H. McDermott
NeuroImage – Volume 129, 1 April 2016, Pages 401–413
doi: 10.1016/j.neuroimage.2016.01.050

Neural responses to grammatically and lexically degraded speech
Alexa Bautista & Stephen M. Wilson
Language, Cognition and Neuroscience – Published online: January 20, 2016
doi: 10.1080/23273798.2015.1123281

Acoustic richness modulates the neural networks supporting intelligible speech processing
Yune-Sang Lee, Nam Eun Min, Arthur Wingfield, Murray Grossman, Jonathan E. Peelle
Hearing Research – Volume 333, March 2016, Pages 108–117
doi: 10.1016/j.heares.2015.12.008

Show Published Studies From 2010-2015

S14 earphones are currently in use at these, and other, research institutions:

Carl von Ossietzky Universitat Oldenburg

Oldenburg, Germany

Children’s Hospital Boston

Boston, Massachusetts USA

Donders Institute for Brain, Cognition and Behaviour

Nijmegen, The Netherlands

Harvard University – Center for Brain Science

Cambridge, Massachusetts USA

INSERM – National Institute for Medical Research

Paris, France

Martinos Center for Biomedical Imaging, Massachusetts General Hospital

Charlestown, Massachusetts USA

Massachusetts Institute of Technology

Cambridge, Massachusetts USA

Max Planck Institute for Human Cognitive and Brain Sciences

Leipzig, Germany

Medical Research Council Institute of Hearing Research

Nottingham, United Kingdom

Medical University of South Carolina

Charleston, South Carolina USA

Montreal Neurological Institute and Hospital at McGill University

Montreal, Canada

Princeton Neuroscience Institute

Princeton, New Jersey USA

University of Glasgow

Glasgow, Scotland

University of Oxford

Oxford, United Kingdom

Downloads

EQ Filtering 4.0 (64bit) – Windows® XP/Vista/7/8/10 – March 2021

EQ Filtering 4.0 Instructions (PDF) – March 2021

Notes: All users are encouraged to download and install EQ Filtering version 4.0. Please uninstall any earlier versions of EQ Filtering before running this installer. Windows® XP/Vista/7/8/10 users, after downloading, please right-click the setup file and click “Install as Administrator” or install with UAC (User Account Control) disabled.

Matlab Functions for Loading S14 Filters – October 2022

For 32-bit or legacy support, existing users may continue to use EQ Filtering version 2.2 (links below).

EQ Filtering 2.2 (32bit) – Windows® XP/Vista/7/8/10 – July 16, 2012

EQ Filtering 2.2 (64bit) – Windows® XP/Vista/7/8/10 – July 16, 2012