Biomedical subjects

Marc A Maier

Publications and source records attributed to Marc A Maier.

4 recordsLinked to original sources

PubMed2004

Direct and indirect pathways for corticospinal control of upper limb motoneurons in the primate.

In the macaque monkey and in humans, the monosynaptic cortico-motoneuronal system is well developed. It allows the cortical motor areas to make an important direct contribution to the pattern of muscle activity during upper limb movements. There is, in addition, good anatomical evidence for descending corticospinal inputs being able to influence the premotoneuronal networks of the cervical spinal cord, and especially those operating at the segmental level of upper limb motoneurons. While oligosynaptic inhibition has been easy to demonstrate in the macaque, and may be a very important component of descending corticospinal control, it has proved much more difficult to detect signs of oligosynaptic excitation. In contrast, in the squirrel monkey, in which the cortico-motoneuronal system is far less developed, oligosynaptic excitation is prominent. There are important changes in the interplay between direct and indirect pathways in different primates, which may provide important clues on the nature of the corticospinal control of upper limb function.

Animals↗

PubMed2004

Temporal processing in primate motor control: relation between cortical and EMG activity.

We investigated spatio-temporal information processing in the primate motor system. Corticomotoneuronal (CM) cells provide monosynaptic excitatory connections from motor cortex to spinal motoneurons and contribute causally to the time-varying electromyogram (EMG) of their target muscle. A multilayer perceptron (MLP) was used to evaluate the transfer function between neural activity of single CM cells and their target muscle EMG, using data from in-vivo recordings in primate motor cortex. For an optimal MLP performance, i.e., minimal error between recorded target EMG and MLP-derived EMG, the CM cell input period had to span the latency observed between CM cell peak activity and EMG peak activity. We argue that the same spike train may code two types of information: 1) rate coding within the input window accounted for large-amplitude variations in the EMG signal and 2) temporal coding within a window of 40 ms just prior to the EMG output signal accounted for EMG variations of small amplitude. The transfer function of the MLP, thus, combines rate and temporal coding and suggests that CM cell output may also combine these two forms of coding. We predict that mutual constraints of rate and temporal coding would, however, would limit the CM output to code for particular temporal profiles of EMG, possibly adapted to bio-mechanical constraints.

Action Potentials↗

PubMed2004

Cortical reorganization allows for motor recovery after crossed cerebrocerebellar atrophy.

The authors report the case of a 33-year-old woman who exhibited, at the age of 17, a left-sided hemiplegia, which was followed by good motor recovery, though with a permanent deficit in fine finger movements. She had a widespread loss of neural tissue in the right hemisphere (crossed cerebrocerebellar atrophy), including (1) marked atrophy and thinning of the precentral and postcentral gyri; (2) widespread deep white matter destruction, including the corticospinal tract; and (3) crossed cerebellar atrophy. Except over the supplementary motor area (SMA), transcranial magnetic stimulation did not elicit motor evoked potentials in the affected hand. Nevertheless, during opening and closing of the affected hand, functional magnetic resonance imaging showed an activation of the lesioned primary sensorimotor cortex (SMC), as well as of the intact SMA and the parietal areas, but not of the ipsilateral motor areas. The authors speculate that recovery was achieved by a motor command generated in the SMC and the parietal cortex, passing through corticospinal axons originating in the SMA.

Adult↗

PubMedDate not supplied

Recurrent neural networks of integrate-and-fire cells simulating short-term memory and wrist movement tasks derived from continuous dynamic networks.

Dynamic recurrent neural networks composed of units with continuous activation functions provide a powerful tool for simulating a wide range of behaviors, since the requisite interconnections can be readily derived by gradient descent methods. However, it is not clear whether more realistic integrate-and-fire cells with comparable connection weights would perform the same functions. We therefore investigated methods to convert dynamic recurrent neural networks of continuous units into networks with integrate-and-fire cells. The transforms were tested on two recurrent networks derived by backpropagation. The first simulates a short-term memory task with units that mimic neural activity observed in cortex of monkeys performing instructed delay tasks. The network utilizes recurrent connections to generate sustained activity that codes the remembered value of a transient cue. The second network simulates patterns of neural activity observed in monkeys performing a step-tracking task with flexion/extension wrist movements. This more complicated network provides a working model of the interactions between multiple spinal and supraspinal centers controlling motoneurons. Our conversion algorithm replaced each continuous unit with multiple integrate-and-fire cells that interact through delayed "synaptic potentials". Successful transformation depends on obtaining an appropriate fit between the activation function of the continuous units and the input-output relation of the spiking cells. This fit can be achieved by adapting the parameters of the synaptic potentials to replicate the input-output behavior of a standard sigmoidal activation function (shown for the short-term memory network). Alternatively, a customized activation function can be derived from the input-output relation of the spiking cells for a chosen set of parameters (demonstrated for the wrist flexion/extension network). In both cases the resulting networks of spiking cells exhibited activity that replicated the activity of corresponding continuous units. This confirms that the network solutions obtained through backpropagation apply to spiking networks and provides a useful method for deriving recurrent spiking networks performing a wide range of functions.

Animals↗