Listening to speech with a guinea pig-to-human brain-to-brain interface.

Nicolelis wrote in his 2003 review on brain-machine interfaces (BMIs) that the design of a successful BMI relies on general physiological principles describing how neuronal signals are encoded. Our study explored whether neural information exchanged between brains of different species is possible, similar to the information exchange between computers. We show for the first time that single words processed by the guinea pig auditory system are intelligible to humans who receive the processed information via a cochlear implant. We recorded the neural response patterns to single-spoken words with multi-channel electrodes from the guinea inferior colliculus. The recordings served as a blueprint for trains of biphasic, charge-balanced electrical pulses, which a cochlear implant delivered to the cochlear implant user's ear. Study participants completed a four-word forced-choice test and identified the correct word in 34.8% of trials. The participants' recognition, defined by the ability to choose the same word twice, whether right or wrong, was 53.6%. For all sessions, the participants received no training and no feedback. The results show that lexical information can be transmitted from an animal to a human auditory system. In the discussion, we will contemplate how learning from the animals might help developing novel coding strategies.

The effects of short-term computerized speech-in-noise training on postlingually deafened adult cochlear implant recipients.

PURPOSE: To determine if short-term computerized speech-in-noise training can produce significant improvements in speech-in-noise perception by cochlear implant (CI) recipients on standardized audiologic testing measures. METHOD: Five adult postlingually deafened CI recipients participated in 4 speech-in-noise training sessions using the Seeing and Hearing Speech program (Sensimetrics; Malden, MA). Each participant completed lessons concentrating on consonant and vowel recognition at word, phrase, and sentence levels. Speech-in-noise abilities were assessed using the QuickSIN (Killion, Niquette, Gudmundsen, Revit, & Banerjee, 2004) and the Hearing in Noise Test (HINT ( Nilsson, Soli & Sullivan, 1994)). RESULTS: All listeners significantly improved key word identification on the HINT after training, albeit only at the most favorable signal-to-noise ratio (SNR). Listeners also showed a significant reduction in the degree of SNR loss on the QuickSIN after training. CONCLUSION: Short-term speech-in-noise training may improve speech-in-noise perception in postlingually deafened adult CI recipients.