|Publication number||WO2000027280 A1|
|Publication date||18 May 2000|
|Filing date||5 Nov 1999|
|Priority date||6 Nov 1998|
|Publication number||PCT/1999/1042, PCT/CA/1999/001042, PCT/CA/1999/01042, PCT/CA/99/001042, PCT/CA/99/01042, PCT/CA1999/001042, PCT/CA1999/01042, PCT/CA1999001042, PCT/CA199901042, PCT/CA99/001042, PCT/CA99/01042, PCT/CA99001042, PCT/CA9901042, WO 0027280 A1, WO 0027280A1, WO 2000/027280 A1, WO 2000027280 A1, WO 2000027280A1, WO-A1-0027280, WO-A1-2000027280, WO0027280 A1, WO0027280A1, WO2000/027280A1, WO2000027280 A1, WO2000027280A1|
|Inventors||Mandar Jog, Srinivas Kadiyala, Jahangir Nakra|
|Applicant||London Health Sciences Centre|
|Export Citation||BiBTeX, EndNote, RefMan|
|Patent Citations (3), Non-Patent Citations (1), Classifications (4), Legal Events (7)|
|External Links: Patentscope, Espacenet|
A MULTI-CHANNEL DATA ACQUISITION SYSTEM FOR THE REALTIME SPATIAL. TEMPORAL MONITORING AND CLASSIFICATION OF HIGH FREQUENCY BANDWIDTH NEURONAL ACTIVITY
Field Of The Invention
The present invention relates to data acquisition and in particular to a multi-channel data acquisition system and method for the real-time spatial, temporal monitoring and classification of high frequency bandwidth neuronal activity.
Background Of The Invention
Recent advances in functional neurosurgical techniques have given dramatic benefit to patients with Parkinson's disease, tremor and dystonia. The accuracy of surgical target localization appears best to determine the success of these neurosurgical techniques. Surgical targets contain many neurons that have specific neurophysicological electrical properties. Accurate surgical target localization therefore requires the recording of the electrical "signatures" of as many of these neurons as is possible and correlating the electrical signatures with a patient's symptoms and signs before a lesion is made. The use of multi-channel recording electrodes has been shown to increase dramatically the yield of recordable neurons in animals. The task of accurately recording the electrical signatures of the neurons that are picked up by the recording electrodes however, requires a sophisticated, high bandwidth data acquisition system in order to capture the complete waveform of the firing neurons. Although data acquisition systems exist, prior art data acquisition systems have proven to be unsuitable in this environment for large-scale electrophysiological data acquisition.
Accordingly, it is an object of the present invention to provide a novel data acquisition system and method.
Summary Of The Invention According to one aspect of the present invention there is provided a data acquisition system comprising: an interface communicating with at least one transducer sensing neuronal activity of a subject under observation, said interface acquiring neuronal signals output by said at least one transducer and inhibiting ohmic contact between said at least one transducer and said subject; and a data acquisition and processing device coupled to said interface, said data acquisition and processing device capturing and processing neuronal signals acquired by said interface.
According to another aspect of the present invention there is provided a method of acquiring neuronal activity data from a subject comprising the steps of: sensing neuronal signals generated by a subject as said subject performs a task; recording at least one physical condition of said subject during the task performance; and correlating the neuronal signals with the at least one recorded physical condition to yield anatomical information concerning structures from which said neuronal signals originate.
According to still yet another aspect of the present invention there is provided a data acquisition and processing system comprising: a data acquisition and processing device communicating with at least one transducer sensing neuronal activity of a subject under observation during a behavioral event, said data acquisition and processing device capturing neuronal signals output by said at least one transducer during said event; and a behavioral processor recording at least one physical condition of said subject during said event, said behavioral processor conditioning said data acquisition and processing device to capture neuronal signals at selected times corresponding to selected instances during said event.
According to still yet another aspect of the present invention there is provided a data acquisition system comprising: an interface communicating with at least one transducer sensing neuronal activity of a subject under observation, said interface acquiring neuronal signals output by said at least one transducer; and a data acquisition and processing device coupled to said interface, said data acquisition and processing device capturing and processing neuronal signals acquired by said interface, wherein said interface isolates said subject from said data acquisition and processing device.
The present invention provides advantages in that neuronal activity and behavioral events such as associated motor activity of a subject can be recorded. The sorted and classified neuronal and motor activity data can be directly input to analysis software that performs on-line power spectral analysis, statistical quantification and spatial mapping in four dimensional space. The spatio-temporal and neurophysiological characteristics of the recorded neurons can then be used to provide anatomical information about the structures from which the neuronal signals originate thereby allowing the surgical target to be determined directly. Further detailed analysis of the acquired data can also be performed off-line. As a result, the data acquisition system enhances the ability of caregivers and researchers to pinpoint the functional relationships of tasks performed by subjects to the respective regions of brain activity. Accordingly, the data acquisition system provides a valuable addition to the functional and neurosurgical and physiological arsenal in active visualization of brain functions.
In addition, the present invention also provides advantages in that chronic transducer bundles, after implantation in a subject's brain, can be monitored. Specific channels from the transducer bundles can then be selected so that only areas of interest are monitored thereby to enhance patient results.
Brief Description Of The Drawings
An embodiment of the present invention will now be described more fully with reference to the accompanying drawings in which: Figure 1 is a schematic diagram of a data acquisition system in accordance with the present invention; and
Figure 2 is a schematic diagram of an RSI amplifier array and a data acquisition and processing device forming part of the data acquisition system of Figure
Detailed Description Of The Preferred Embodiment
The present invention relates to a multi-channel data acquisition system for the real-time spatial, temporal monitoring and classification of high frequency bandwidth neuronal activity. The data acquisition system allows biological functionality to be deterministically associated with spatial and temporal neural activity and provides data which can be processed to provide anatomical information about the structures from which neuronal signals originate. As a result, surgical targets can be determined directly. Turning now to Figure 1, the data acquisition system is shown and is generally indicated to by reference numeral 10. As can be seen, the data acquisition system 10 includes a patient interface 12, signal processing circuitry 14 coupled to the patient interface 12 and to a data acquisition and processing device 16, and a behavioral processor 18 communicating with the data acquisition and processing device 16.
Patient interface 12 is coupled to a plurality of transducer bundles 20. Each transducer bundle 20 includes four closely spaced electrodes (not shown) mounted on a recording probe (not shown). The recording probes are acutely or chronically implanted in a subject's brain and pick up analog neuronal signals of interest. Since each recording probe includes four closely spaced electrodes, each recording probe is capable of capturing a neuronal electrical event simultaneously on four channels providing a four dimensional view of the neuronal electrical event.
The patient interface 12 includes a preamplifier 24 to amplify the neuronal signal output of the transducer bundles 18, a programmable multiplexer 26 to multiplex the amplified multi-channel neuronal signal output of the transducer bundles 18 onto a twisted shielded cable 28 to inhibit noise contamination, and a patient isolation interface device 30. The patient isolation interface device 30 acts between a power supply 32 and the recording probes and includes unidirectional buffer circuits that inhibit backward current leakage from downstream hardware into a subject. Thus, the patient isolation interface device inhibits ohmic contact between the transducer bundles 18 and a subject's brain. The preamplifier 24, multiplexer 26 and patient isolation interface device 30 are integrated to form a streamlined arrangement that facilitates interfacing with a subject thereby allowing neuronal activity to be measured in many environments such as the operating room or chronically. This streamlined arrangement also allows for short wire lengths between the preamplifier 16 and the multiplexer 26 thereby reducing signal loss and noise contamination.
The signal processing circuitry 14 includes a demultiplexer 40 that is synchronized with the multiplexer 26. The demultiplexer 40 demultiplexes the neuronal signals carried on the shielded cable 28 and outputs the neuronal signals onto output channels corresponding in number to the input channels of the multiplexer 26. The signal processing circuitry 14 also includes an RSI amplifier array 42 including high-gain, high bandwidth, programmable differential instrumentation amplifiers and software programmable precision bandpass filters. The amplifiers of the RSI amplifier array 42 amplify the neuronal signals to signal level values that are recognizable by the data acquisition and processing device 16. The bandpass filters of the RSI amplifier array 42 filter the neuronal signals to eliminate selectively parts of the neuronal signals in order to highlight measured signal characteristic features.
The RSI amplifier array 42 is highly modularized and includes multiple amplification cards placed on a common back plane. A built-in regulated power supply (not shown) provides necessary power to the amplification cards. The back plane can hold up to 12 amplification cards. Each amplification card has the capacity to amplify the neuronal signals from one recording probe (i.e. neuronal signals on four channels). By adding amplification cards to the back plane, the channel capability of the RSI amplifier array 42 can be increased making the RSI amplifier array scalable.
Each amplification card includes two cascaded amplifying stages per channel to preserve the high bandwidth of the neuronal signals. The gain of each amplifying stage can be programmed through the data acquisition and processing device 16 and can be set to a gain equal to 1, 10, 100 or 1,000. Since each amplification card provides two amplifying stages per channel, the amplification factor of each amplification card can be set to a gain equal to 1,100, 10,000 or 1,000,000. Although the amplification cards have the capability of amplifying a signal up to 1,000,000 times, this final amplification value is deliberately inhibited by the data acquisition and processing device 16.
The data acquisition and processing device 16 in the preferred embodiment includes an IBM compatible personal computer 50 running Windows NT (see Figure 2). Two high-end data acquisition cards, collectively identified by reference numeral 52, such as those manufactured by Innovative Integration under number ADC64, are installed in the personal computer 50. The data acquisition cards 52 have high-end digital signal processors (DSPs, not shown) as well as eight 16-bit analog to digital converters (ADCs) 54 that convert signals from the analog domain to the digital domain.
The personal computer 50 executes data acquisition software. The code of the data acquisition software is split into two components, namely host code 56 and target code 58. The host code 56 deals with personal computer functionality while the target code 58 deals with data acquisition card functionality. The host code 56 runs on the personal computer under NT and provides the "front end" or user interface. The target code 58 runs on the data acquisition cards 52 and performs "back end" tasks.
The target code 58 is written in TI C32 DSP Assembly and C. The portion of the target code 58 written in C handles low speed system setting issues and initialization. The portion of the target code 58 written in Assembly runs in a tight loop and forms the basis for a data acquisition algorithm. The data acquisition algorithm is responsible for the task of sampling and multiplexing neuronal signals output by the RSI amplifier array 42 into the ADCs 54. The Assembly target code 58 also performs "thresholding". Thresholding ensures that the data acquisition cards 52 grab data from the ADCs 54, only if the amplitudes of the neuronal signals received from the RSI amplifier array 42 swing above or below a user defined threshold.
In addition, the target code 58 accesses pre-established neuronal signal patterns stored in memory. The target code 58 can be conditioned to compare sampled neuronal signals with the pre-established neuronal signal patterns and generate scores reflecting the degree of similarity between sampled neuronal signals and the pre- established neuronal signal patterns.
The host code 56 is written in Visual C++ and provides a user with control options via a graphical user interface. The host code 56 grabs data sent to it by the target code 58, analyses and plots the data and saves the data to hard disk on cue from a user command. The plots generated by the host code 56 show neuronal signal waveforms and the power spectrum of the neuronal signal waveforms. Additionally, the host code 56 allows the user to set the gains on the data acquisition cards 52, the gains for the amplifiers of the RSI amplifier array 42, the bandpass filter cut-off frequencies for the RSI amplifier array 42 and the active input channels of the multiplexer 26. In this embodiment, the upper and lower cut-off frequencies of the bandpass filters can be programmed in the range from about 9 kHz to 100 Hz. The host code 56 also allows the user to set the target code threshold.
The behavioral processor 18 communicates with a plurality sensors 66, which monitor the subject under observation as the subject performs physical tasks, and records one or more physical conditions of the subject during task performance. In this particular embodiment, the sensors 66 include a video recorder, an audio recorder and accelerometers to measure limb movement. Those of skill in the art will however appreciate that other types of sensors can be used to monitor the subject. The behavioral processor 18 triggers the data acquisition and processing device 16 so that neuronal activity data acquisition is synchronized with the behavioral events of the subject that are recorded by the behavioral processor 18. The operation of the data acquisition system 10 will now be described.
During initialization, the host code 56 checks for the presence of the data acquisition cards 52 in the personal computer 50. When the data acquisition cards are present, the host code downloads the target code 58 onto the data acquisition cards 52 and sets up a "handshaking" mechanism between the host code 56 and the target code 58 to enable data and command transfer between the host code 56 and the data acquisition cards 52.
During operation, recording probes are implanted in the subject's brain. Since each recording probe includes four electrodes, each recording probe acquires neuronal activity at an area of interest in four dimensions. The sensors 66 are also initialized to monitor behavioral events of the subject under observation. The subject is then requested to perform tasks. During task performance, the behavioral processor 18 records the output of the sensors 66. The behavioral processor 18 also sends "acquire" and "stop-acquire" signals to the data acquisition device and processing device 16 at selected times during task performance so that neuronal activity, corresponding to selected instances of subject motor activity, is acquired over the desired durations. These durations may be from several seconds to several minutes in duration.
During task performance, the neuronal signal output of the transducer bundles 18 are conveyed to the preamplifier 16. The preamplifier 16 in turn amplifies the neuronal signals to signal levels in the range of from about 0 to ± lOv to reduce signal loss either by decreasing the output impedance to increase current or by providing gain to increase voltage and current. The amplified neuronal signals output by the preamplifier 16 are applied to the input channels of the multiplexer 26. The neuronal signals received on the active input channels of the multiplexer 26 are multiplexed onto the shielded twisted cable 28 before being conveyed to the patient isolation interface device 30. As mentioned previously, the patient isolation interface device 30 inhibits ohmic contact between the transducer bundles 18 and the subject's brain.
The neuronal signal output of the patent isolation interface device 30 is conveyed to the demultiplexer 40 via the cable 28 and demultiplexed onto its output channels. The RSI amplifier array 42 in turn boosts the signals appearing on the output channels of the demultiplexer 40 by providing EMI and RF noise regeneration in the neuronal signals in accordance with the values assigned to the programmable gains of the amplifiers by the data acquisition and processing device 16. The RSI amplifier array 42 also removes selected parts of the neuronal signals via the bandpass filters as programmed by the data acquisition and processing device 16. The amplified and filtered neuronal signals output by the RSI amplifier array 42 are then conveyed to the data acquisition and processing device 16.
When the data acquisition and processing device 16 is triggered by an acquire signal from the behavioral processor 18, the target code 58 is executed. When the target code 58 is executed, the data acquisition cards 52 step through the data acquisition algorithm. During this algorithm, the neuronal signal output of the RSI amplifier array 42 is sampled at a rate equal to about 30 kHz (resultant) and the neuronal signals are multiplexed into the ADCs 54. The neuronal signals are in turn digitized by the ADCs 54. During execution of the target code 58, thresholding is also performed by comparing the digital values output by the ADCs 54 with the user set threshold.
If the digital values on one or more of the RSI amplifier array output channels swing above or below the threshold signifying potentially relevant neuronal signals, the data acquisition cards 52 capture the digital values for a predetermined period of time, in this example 1-2 msecs. Specifically, the data acquisition cards store the previous eight (8) sampled values in addition to the next twenty-four (24) sampled values. This is achieved by using circular buffers to store the sampled data while it is being acquired. For the acquisition of data to take place at 30KHz, the Assembly target code 58 performs an acquisition once every 90KHz. If the target code 58 is conditioned to compare incoming neuronal signals with the pre-established neuronal signal patterns stored in memory, the target code 58 compares the digital values with each of the stored patterns and generates scores. The sampled digital values, the threshold information signifying the transducer that generated the neuronal signal which caused the digital value to be sampled, and the scores, if calculated, form a data packet. Once seven data packets are grabbed by the data acquisition cards 52, the data packets are transferred in bursts or streams to the host code 56 via a PCI bus within the personal computer 30 and stored in permanent memory. A burst is sent per PCI bus mastering operation for a total data throughput of 20 Mbs, a rate well under the permissible PCI bus transfer limit of 60 Mbs.
The host code in turn processes the data on-line by performing power spectral analysis, statistical quantification and spatial mapping in four dimensions. Thus, real time feedback can be provided to improve surgical targets and to modify the active channels of the multiplexer 26. The data stored in memory can also be downloaded to an off-line neural data analysis system 80 for further processing.
When the duration of the relevant behavioral event has expired, the behavioral processor 18 sends a "stop-acquire" signal to the data acquisition and processing device 16 causing it to stop the data acquisition. At this point the neuronal signals output by the transducer bundles 18 are no longer recorded.
The above-described form of data gathering accomplishes two goals. Firstly, the temporal sequence of neuron firing is clearly established relative to the stages of the behavioral event of interest. Secondly, the spatial location of each of these neurons firing in sequence is clearly established by the bundled electrodes of the recording probes. The collected data is readily available for processing by data analysis techniques to yield insight into the nature of the neural activity in relationship to behavioral patterns. This immediate data analysis can be used to determine the properties of recorded neuronal activity and therefore, increase the accuracy of surgical targets, which of course aids in patient treatment.
Although a preferred embodiment of the present invention has been described, those of skill in the art will appreciate that variations and modifications may be made without departing from the spirit and scope thereof as defined by the appended claims.
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|Cooperative Classification||G16H10/60, G16H40/63|
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