Somatotopic Mapping of the Fingers in the Somatosensory Cortex Using Functional Magnetic Resonance Imaging: A Review of Literature.

Multiple studies have demonstrated finger somatotopy in humans and other primates using a variety of brain mapping techniques including functional magnetic resonance imaging (fMRI). Here, we review the literature to better understand the reliability of fMRI for mapping the somatosensory cortex. We have chosen to focus on the hand and fingers as these areas have the largest representation and have been the subject of the largest number of somatotopic mapping experiments. Regardless of the methods used, individual finger somatosensory maps were found to be organized across Brodmann areas (BAs) 3b, 1, and 2 in lateral-to-medial and inferior-to-superior fashion moving from the thumb to the pinky. However, some consistent discrepancies are found that depend principally on the method used to stimulate the hand and fingers. Therefore, we suggest that a comparative analysis of different types of stimulation be performed to address the differences described in this review.

Precise finger somatotopy revealed by focal motor cortex injury.

BACKGROUND: Somatotopy is considered the hallmark of the primary motor cortex. While this is fundamentally true for the major body parts (head, upper and lower extremities), evidence supporting the existence of within-limb somatotopy is scarce. METHOD: We report a young man presenting recurrent ischemic strokes with selective finger weakness in whom serial motor cortex mapping procedures were performed. RESULT: Following the first stroke, which largely spared the motor cortex, motor mapping displayed overlap of the motor representations of the hand muscles. The second focal stroke, affecting the lateral part of the hand knob, resulted in selective loss of the first dorsal interosseous muscle motor evoked potentials while sparing those of the adductor digiti minimi muscle. This observation is in apparent contradiction with the first mapping results that suggested complete overlap of motor representations. DISCUSSION: Our mapping results provide evidence for the existence of very precise within-limb somatotopy and confirm the proposed homuncular order, whereby lateral fingers are represented laterally and medial fingers medially. The discrepancy between the initial and subsequent mapping results is discussed in light of functional organization of the primary motor cortex.

High Spatiotemporal Resolution ECoG Recording of Somatosensory Evoked Potentials with Flexible Micro-Electrode Arrays.

Electrocorticogram (ECoG) has great potential as a source signal, especially for clinical BMI. Until recently, ECoG electrodes were commonly used for identifying epileptogenic foci in clinical situations, and such electrodes were low-density and large. Increasing the number and density of recording channels could enable the collection of richer motor/sensory information, and may enhance the precision of decoding and increase opportunities for controlling external devices. Several reports have aimed to increase the number and density of channels. However, few studies have discussed the actual validity of high-density ECoG arrays. In this study, we developed novel high-density flexible ECoG arrays and conducted decoding analyses with monkey somatosensory evoked potentials (SEPs). Using MEMS technology, we made 96-channel Parylene electrode arrays with an inter-electrode distance of 700 µm and recording site area of 350 µm2. The arrays were mainly placed onto the finger representation area in the somatosensory cortex of the macaque, and partially inserted into the central sulcus. With electrical finger stimulation, we successfully recorded and visualized finger SEPs with a high spatiotemporal resolution. We conducted offline analyses in which the stimulated fingers and intensity were predicted from recorded SEPs using a support vector machine. We obtained the following results: (1) Very high accuracy (~98%) was achieved with just a short segment of data (~15 ms from stimulus onset). (2) High accuracy (~96%) was achieved even when only a single channel was used. This result indicated placement optimality for decoding. (3) Higher channel counts generally improved prediction accuracy, but the efficacy was small for predictions with feature vectors that included time-series information. These results suggest that ECoG signals with high spatiotemporal resolution could enable greater decoding precision or external device control.