Functional connectivity in auditory cortex using chronic, multichannel unit recordings.

Bioengineering Program, Arizona State University, Tempe, AZ 85287-6006, USA
Neurocomputing (Impact Factor: 2.01). 06/1999; 26-27:347-354. DOI: 10.1016/S0925-2312(99)00023-5
Source: DBLP

ABSTRACT Chronic, multichannel recordings provide a method for reliable detection and determination of long-term dynamic functional connectivity. Using chronically implanted multichannel electrode arrays, we simultaneously recorded 30–70 units in guinea pig auditory cortex in daily recording sessions for implant durations of six months. We examined stimulus response properties and correlation strengths in neuron pairs in four animals. Preliminary results from these `snapshots’ of functional connectivity suggest sparse functional connections among widely distributed neurons. Some of these functional connections were found to persist for several days. These results provide a framework upon which further investigations of functional dynamic connectivity can be developed.

  • [Show abstract] [Hide abstract]
    ABSTRACT: The Korean Brain Neuroinformatics Research Program has dual goals, i.e., to understand the information processing mechanism in the brain and to develop intelligent machine based on the mechanism. The basic form of the intelligent machine is called Artificial Brain, which is capable of conducting essential human functions such as vision, auditory, inference, and emergent behavior. By the proactive learning from human and environments the Artificial Brain may develop oneself to become more sophisticated entity. The OfficeMate will be the first demonstration of these intelligent entities, and will help human workers at offices for scheduling, telephone reception, document preparation, etc. The research scopes for the Artificial Brain and OfficeMate are presented with some recent results.
    05/2007: pages 123-143;
  • [Show abstract] [Hide abstract]
    ABSTRACT: By applying independent component analysis (ICA) algorithm to auditory signals a computational model was developed for the speech feature extraction at the primary auditory cortex. Unlike the other ICA-based features with simple frequency selectivity at the basilar membrane and inner hair cells the learnt features represent complex signal characteristics at the primary auditory cortex such as onset/offset and frequency modulation in time. Also, the topology is preserved with the help of neighborhood coupling during the self-organization. The extracted complex features demonstrated good performance for the robust discrimination of speech phonemes.
    Neurocomputing 06/2005; 65:793-800. · 2.01 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Chronic multichannel neural recording has emerged as a powerful technique for studying dynamic brain function. In many experimental paradigms, it is important that the same neurons be recorded from day to day. The objective of this study was to develop methods for tracking the recorded neural population over time through analysis of unit waveforms, principle component clusters and response properties of single units and multiunit clusters. We demonstrate that these techniques can be used to provide a useful measure of unit stability over extended recording periods.
    Neurocomputing 06/1999; · 2.01 Impact Factor