- Research article
- Open Access
Stimulus-dependent spatial patterns of response in SI cortex
© Chiu et al; licensee BioMed Central Ltd. 2005
- Received: 09 February 2005
- Accepted: 19 July 2005
- Published: 19 July 2005
Recently we reported that vibrotactile flutter stimulation of a skin locus at different amplitudes evokes an optical response confined to the same local region of the primary somatosensory cortex (SI), where its overall magnitude varies proportionally to the flutter amplitude. In this report, we characterize the impact of the flutter amplitude on the spatial patterns of activity evoked within the responding SI region.
In order to characterize the spatial pattern of activity within the responding SI region, images of the flutter-evoked SI optical response were segmented and analyzed with spatial frequency analysis. The analysis revealed that: (1) dominant spatial frequencies in the optical intrinsic signal emerge within the responding SI region within 3–5 sec of stimulus onset; (2) the stimulus-evoked activity is spatially organized in a form of several roughly parallel, anterior-posteriorly extended waves, spaced 0.4–0.5 mm apart; (3) the waves themselves exhibit spatial periodicities along their long axis; and (4) depending on the flutter stimulus amplitude, these periodicities can range from fine 0.15 mm "ripples" at 50 μm amplitude to well-developed 0.5 mm fluctuations at the amplitude of 400 μm.
The observed spatiointensive fractionation on a sub-macrocolumnar scale of the SI response to skin stimulation might be the product of local competitive interactions within the stimulus-activated SI region and may be a feature that could yield novel insights into the functional interactions that take place in SI cortex.
- Spatial Frequency
- Lower Spatial Frequency
- Stimulus Amplitude
- Spatial Periodicity
- Optical Intrinsic Signal
Afferent projections from skin to primary somatosensory cortex (SI) are well known to form a fine map of the body surface in SI. In this map, a skin locus provides afferent input to an extensive cortical region in SI [1, 2]. In particular, the direct connectivity between somatosensory thalamus and SI cortex is now recognized to be much more spatially distributed than previously believed (e.g., in primates the ventrobasal thalamic region which receives its input from a single digit projects to an extensive, 20 mm2 sector of SI cortex – [3, 4]). The intrinsic SI excitatory connections link not only neighboring but also widely separated regions of somatosensory cortex . These connections ensure that many members of widely distributed neuronal populations interact extensively within milliseconds after the onset of stimulus-evoked thalamocortical drive. Thus it is not surprising to find that the processing of even a very local skin stimulus is associated with SI activation over several sq. millimeters of cortical area, as revealed, for example, with optical imaging techniques [6–10].
Such spatially extensive cortical regions are not functionally homogeneous. For example, using Optical Intrinsic Signal (OIS) imaging in near-infrared (830 nm) range, we find that in squirrel monkeys a small-diameter stimulus probe oscillating on the skin at 25 Hz activates more than 3 mm2 of cortical territory in area 3b of SI [6, 8, 11]. Such a territory can contain as many as 20 place-defined cortical columns ("segregates"; ) organized into 4–6 alternating rapidly- and slowly-adapting submodality bands . Chen et al.  reported that the relative magnitudes of optical response in local, 0.2–0.4 mm wide, SI regions changes when the frequency of the stimulating probe is changed from simple taps to 25 Hz to 200 Hz (thus preferentially activating different submodalities of skin mechanoreceptors). And on even finer spatial scale SI might be organized in ~50 μm-diameter functionally distinct minicolumns [1, 12, 14–18].
Together these considerations suggest that the spatial pattern of activity evoked in SI by even the smallest stimuli might be structurally more complex than a typically envisioned basic bell-shaped pattern. A closer inspection of such patterns might reveal certain spatial formations within them with significant functional implications. Recently, we investigated the response of SI cortex to varying amplitudes of flutter stimulation. Regardless of the amplitude of stimulation (in the range of 50 to 400 μm), we found that the spatial extent of the response of SI cortex remained the same . Instead, the actuated cortical region exhibits increases in its magnitude of neuronal response proportional to the intensity of stimulation [19–21]. One feature of particular interest in our study was that the activity patterns evoked within these spatially delineated regions, when viewed at high resolution, appeared to develop in an orderly manner dependent on stimulus amplitude. The purpose of this study was to determine if those patterns are indeed systematic, and if so, to characterize them quantitatively.
Figure 8C plots the magnitude of OIS response to the 50 μm- and 400 μm-amplitude stimuli as a function of time after the stimulus onset, showing that during the time when the dominant spatial frequency migrates across the power spectrum, the OIS also grows overall in its magnitude. The concurrency of these changes raises a parsimonious possibility that OIS periodicity is a direct function of the OIS magnitude (and thereby only an indirect function – via their control of the OIS magnitude – of the stimulus strength and duration). To evaluate this possibility, Figure 8D plots the highest-power spatial frequency at any given time (taken from Figure 8A plot) as a function of the overall OIS magnitude at that time (taken from the Figure 8C plot). As the Figure 8D plot shows, the relationship between OIS magnitude and periodicity obtained with the 50 μm-amplitude stimuli appears to be different from the relationship obtained with the 400 μm stimuli, suggesting that OIS periodicity cannot be explained simply by the overall OIS magnitude.
Spatial frequency analysis revealed that the SI response to flutter stimulation produces systematic, spatially periodic fluctuations in the magnitude of the OIS within the responding SI region. In the absence of stimulation – the control condition – the power spectra have a small prevalence of spatial periodicities in the range of 0.1–0.14 mm. In contrast, in the presence of a prominent flutter stimulus spatial periodicities in the range of 0.4–0.6 mm dominate the stimulus-activated SI region.
Visual inspection of the 3-D activity plots (Figures 1, 2, 3, 6), together with the results of spectral analyses performed along the anterior-posterior and medial-lateral cortical dimensions, point to a substantial tendency of the stimulus-evoked activity to take a form of a pattern of roughly parallel elongated waves oriented in the anterior-posterior direction. These waves have a medio-lateral spacing of 0.4–0.5 mm between their crests. This tendency is already well developed in response to a relatively weak, 50 μm-amplitude flutter. At such weaker stimuli, each anterior-posteriorly oriented wave has a pattern of fine "ripples" along its long axis, with the dominant spatial periodicities in the neighborhood of 0.15-0.2 mm – values close to those characteristic of the OIS in the no-stimulus condition. Stronger stimuli lead to an emergence of larger spatial periodicities in the anterior-posterior dimension, up to 0.6 mm. Such a stimulus amplitude-dependent shift towards larger spatial periodicities suggests that the spatial pattern of SI response to flutter stimulation undergoes substantial reorganization in response to changes in stimulus amplitude/intensity. That is, the stronger (200–400 μm amplitude) stimuli have an effect of restructuring the anterior-posteriorly oriented waves by replacing the high-frequency ripples along their crests with more prominent ca. 0.5 mm periodic fluctuations.
Such a reorganization of stimulus-evoked OIS spatial patterns apparently also occurs across time. That is, flutter stimulus-evoked OIS patterns in the anterior-posterior dimension develop gradually from the resting state – dominated by high spatial frequencies – through a series of states characterized by progressively lower spatial frequencies. Thus, the spatial organization of the patterned response evoked in SI by a flutter stimulus varies with both stimulus strength and stimulus duration.
In interpreting the outcomes of our spatial frequency analyses, it is important that it be recognized that they were performed not on the SI neuroelectrical responses to flutter stimulation, but on SI optical responses to such stimulation. It now is well established that cortical neuroelectrical activity is positively and strongly correlated with the local increase in cortical tissue light absorbance [8, 11, 22–27]. Although highly correlated with neuroelectrical activity, however, the OIS is not a direct reflection of either neuronal spike discharge activity or, more generally, the local voltage changes evoked by a sensory stimulus. Notably, it has a much slower onset and decay than the neuroelectrical responses of cortical cells. The intrinsic signal detected using the near-infrared light ("IR imaging") is relatively independent of changes in blood flow [28, 29]. The optical signal observed under near-infrared light reflects a variety of factors but, most significantly, change (shrinkage) in the volume of the extracellular fluid compartment attributable to the glial swelling due to stimulus-evoked changes in extracellular [K+] and/or neurotransmitter release [23, 30, 31]. In view of these complex origins of the near-infrared OIS, it remains to be determined whether the observed stimulus-dependent periodicities reflect the spatial organization of stimulus-evoked neuroelectrical activity. Alternatively, the observed OIS periodicities might reflect the spatial organization of the cortical glial reaction to local neuroelectrical activity, or SI microvascular responses , which become more prominent with increases in both stimulus strength and duration.
If the observed stimulus-dependent OIS periodicities were to reflect neuroelectrical activity patterns, how well would they fit with the known features of SI functional organization? In particular, a macrocolumnar functional organization has been well documented in SI cortex. Receptive field-mapping techniques have revealed that SI cortex is partitioned into ~0.5 mm-wide submodality- and place-defined columns [1, 2, 12, 13, 33, 34]. These topographic entities, repeating every 0.5 mm, might indeed be responsible for the prominent 0.5 mm periodicity in SI OIS stimulus-evoked activity patterns. If the spatial OIS periodicities were due to selective modulation of entire macrocolumns (in other words, due to SI response fractionation on the macrocolumnar scale), then the observed OIS periodicities would be at least double the size of macrocolumns. Since this is not the case, and the OIS periodicities approximate the size of macrocolumns, the fractionation of the SI response would appear to take place on the submacrocolumnar scale, with flutter stimuli preferentially activating only a subsector of each macrocolumn in the SI region engaged by the stimulus. Such preferentially activated subsectors would then form a roughly periodic pattern across the responding SI region. In support of this proposal, Chen et al.  have reported that single skin taps, 25 Hz flutter, and 200 Hz vibration (stimulus conditions that allow preferential activation of the different classes of skin mechanoreceptors) were associated with preferential activation of different 0.25 mm-diameter regions within the responding SI territory. The small size of these regions suggests that they should occupy only a subsector of a typical submodality column, rather than a whole column .
Whether or not the 0.5 mm periodicities in OIS stimulus-response patterns in SI owe their existence to submodality- and/or place-defined macrocolumns, the fact remains that a flutter stimulus activates multiple cortical loci, separated from each other by less active loci. Such a locally selective distribution of activity in SI is suggestive of the presence in SI functional architecture of a mapping factor in addition to submodality and place on the skin – a factor specific to some yet to be explored attribute(s) of mechanical skin stimulation. Similarly, Bruno and colleagues recently demonstrated that individual barrels in rat SI contain minicolumns of neurons preferring the same whisker deflection angle and that these angular tuning domains could be the result of convergent inputs from thalamocortical cells with corresponding angular preferences . It is possible that upon further investigation, the spatial activity patterns evoked in SI cortex, such as the amplitude-dependent patterns described in this report, will also be found to be submodality-dependent as well.
Finally, considering that spatial periodicities in SI OIS response patterns emerge gradually, and evolve with time after the stimulus onset, the fine sculpting of the SI response might be the result of a network-level neurocomputational process that involves competitive and cooperative interactions among local neuronal aggregates. That is, SI sensitivity to the stimulus attribute(s) responsible for the observed fractionation of activity within the responding SI region might be an emergent property of the SI network (i.e., a product of network-level computation), rather than a simple outcome of selective convergence of thalamocortical afferents on SI neurons.
Observations of the spatial patterns of SI cortical response within an activated region, such as those evoked by flutter stimulation of the skin, suggest that evoked cortical activity within such a territory is not evenly distributed. Furthermore, the cortical activity patterns change in a manner that appears to be dependent upon stimulus conditions. The observed spatiointensive fractionation on a sub-macrocolumnar scale of the SI response to skin stimulation might be the product of local competitive interactions within the stimulus-activated SI region, and as such can lead to new insights about the functional interactions that take place in the SI cortex.
All methods and procedures are consistent with USPHS policies and guidelines on animal care and welfare in biomedical research, and were reviewed and approved in advance by an institutional animal use committee (IACUC). Experiments were conducted in 5 squirrel monkeys. Surgical procedures were carried out under deep general anesthesia (1–4% halothane in a 50/50 mixture of oxygen and nitrous oxide). After induction of anesthesia the trachea was intubated to facilitate positive pressure ventilation and delivery of the gaseous general anesthetic. A catheter was inserted into a branch of the femoral vein of the hindlimb ipsilateral to the hemisphere to be imaged, allowing intravenous (IV) administration of drugs and fluids (5% dextrose and 0.9% NaCl). Methylprednisolone sodium succinate (20 mg/kg) and gentamicin sulfate (2.5 mg/kg) were injected intramuscularly to lessen the probability of halothane-induced cerebral edema and prevent bacterial septicemia, respectively.
A 1.5 cm diameter opening in the skull exposed the forelimb region of SI cortex. A recording chamber was positioned over the opening and cemented to the skull with dental acrylic. The chamber was filled with artificial cerebrospinal fluid, the dura mater overlying SI cortex incised and removed, and all wound margins outside the chamber dressed with long-lasting local anesthetic in oil (Cetacaine). All skin and muscle incisions were closed with sutures and bandaged.
After the completion of all surgical procedures subjects were immobilized with Norcuron (vercuronium bromide; 0.5 mg/kg loading dose; 0. 25-0.5 mg/kg/hr maintenance dose) and ventilated with a gas mixture (a 50/50 mix of oxygen and nitrous oxide; supplemented with 0.5–1.0% halothane). At these concentrations and under normocapnic conditions, halothane has no effect on brain energy metabolism [36, 37], and only minor effects on cerebrovascular regulation . Ventilator rate and volume were adjusted to maintain end-tidal CO2 between 3.0–4.0%. EEG and cardiovascular signs (EEG slow wave content; EKG and heart rate) were monitored continuously, and the anesthetic gas mixture adjusted intermittently to maintain values and reactivity to skin stimuli consistent with light general anesthesia. Rectal temperature was maintained (using a heating pad) at 37.5°C.
The recording chamber was filled with artificial cerebrospinal fluid and hydraulically sealed using a clear glass plate. Vibrotactile stimuli were delivered to selected loci on the hand using a servocontrolled vibrotactile stimulator , capable of delivering precisely controlled sinusoidal vertical skin displacement stimuli. The stimulator made contact with the skin via a cylindrical 2 mm-diameter Delrin probe. All sinusoidal vibrotactile stimuli were superimposed on a static displacement ("pedestal") of 500 μm. Identical parameters of stimulation were used at each skin site that was studied: frequency of vibration 25 Hz (in the flutter range), stimulus duration 7 sec, and interstimulus interval 60 sec. Different peak-to-peak amplitudes of flutter stimulation (0, 50, 100, 200 and 400 μm) were interleaved on a trial-by-trial basis.
The optical imaging system consisted of a computer-interfaced CCD camera, light source, guide and filters required for near-infrared (830 nm) illumination of the cortical surface, a focusing device, and a recording chamber capped by an optical window (for additional methodological details see [7, 40]). Images of the exposed cortical surface were acquired 200 ms before stimulus onset ("reference" or "prestimulus" images) and continuously thereafter ("poststimulus" images; at a resolution of one image/s) for 15s following stimulus onset. Exposure time was 200 ms. Light absorbance images were generated by subtracting each prestimulus (reference) image from a poststimulus image and subsequently dividing by the reference image. Absorbance images obtained in this way typically show regions in which light absorption increases and other regions in which absorption decreases in response to skin stimulation. These regions, respectively, have been shown to correspond to regions in which neuronal activity increases and decreases in response to sensory stimulation ([6, 27, 41–43]; for review see ). Stimulus-evoked OIS responses of SI were displayed as either grayscale images or 3-D surface plots. To reduce amount of noise in these displays, the images were smoothed using a 3 × 3 pixel boxcar filter.
Cortical images were taken at light/time exposures that place the region of interest in the middle of the range of the recorded pixel values. Histogram analysis was used during experimental setup to make sure to avoid any nonlinearities that may arise from overexposure. In some of the experiments the camera was rotated by 90° relative to the SI orientation to better capture the responding cortical field. These rotations did not have any noticeable effect on spectral power distributions along the anterior-posterior and medial-lateral cortical dimensions.
The spatial organization of the stimulus-related light absorbance changes in SI was evaluated using linear image segmentation. This involved segmentation of the relevant region of the image into a linear series of bins and computation of the average absorbance value of the pixels in each bin. The sequence of average absorbance values obtained in this way was plotted as a function of distance (mm) along the cortical path traced by the central points of the series of bins – yielding an absorbance vs. distance plot (thus forming a spatial histogram). Power spectra of the spatial histograms were then computed using Discrete Fourier Transform (DFT) algorithm and plotted as a periodogram. Fourier analysis was always performed on raw, unfiltered images.
At the end of the experiment the subject was euthanized by overdose of pentobarbital (50 mg/kg/IV), followed by intracardial perfusion with saline and 10% formalin.
This work was supported, in part, by US Army Research Office grant P43077-LS (M. Tommerdahl, P.I.), NIH NS050587 (M. Tommerdahl, P.I.) and NIH NS35222 (B. Whitsel, P.I.).
- Favorov OV, Whitsel BL: Spatial organization of the peripheral input to area 1 cell columns: I. The detection of "segregates.". Brain Res. 1988, 472: 25-42.View ArticlePubMedGoogle Scholar
- Favorov OV, Whitsel BL: Spatial organization of the peripheral input to area 1 cell columns: II. The forelimb representation achieved by a mosaic of segregates. Brain Res. 1988, 472: 43-56.View ArticlePubMedGoogle Scholar
- Rausell E, Bickford L, Manger PR, Woods TM, Jones EG: Extensive divergence and convergence in the thalamocortical projection to monkey somatosensory cortex. J Neurosci. 1998, 18 (11): 4216-4232.PubMedGoogle Scholar
- Jones EG: Cortical and subcortical contributions to activity-dependent plasticity in primate somatosensory cortex. Annu Rev Neurosci. 2000, 23: 1-37. 10.1146/annurev.neuro.23.1.1.View ArticlePubMedGoogle Scholar
- Burton H, Fabri M: Ipsilateral intracortical connections of physiologically defined cutaneous representations in areas 3b and 1 of macaque monkeys: projections in the vicinity of the central sulcus. Journal of Comparative Neurology. 1995, 355: 508-538. 10.1002/cne.903550404.View ArticlePubMedGoogle Scholar
- Tommerdahl M, Delemos KA, Favorov OV, Metz CB, Whitsel BL: Response of anterior parietal cortex to different modes of same-site skin stimulation. Journal of Neurophysiology. 1998, 80: 3272-3283.PubMedGoogle Scholar
- Tommerdahl M, Delemos KA, Whitsel BL, Favorov OV, Metz CB: Response of anterior parietal cortex to cutaneous flutter versus vibration. Journal of Neurophysiology. 1999, 82 (1): 16-33.PubMedGoogle Scholar
- Tommerdahl M, Favorov OV, Whitsel BL: Optical imaging of intrinsic signals in somatosensory cortex. Behav Brain Res. 2002, 135: 83-91. 10.1016/S0166-4328(02)00159-6.View ArticlePubMedGoogle Scholar
- Shoham D, Grinvald A: The cortical representation of the hand in macaque and human area S-I: high resolution optical imaging. Journal of Neuroscience. 2001, 21 (17): 6820-6825.PubMedGoogle Scholar
- Chen LM, Friedman RM, Ramsden BM, LaMotte RH, Roe AW: Fine-scale organization of SI (Area 3b) in the squirrel monkey revealed with intrinsic optical imaging. Journal of Neurophysiology. 2001, 86: 3011-3029.PubMedGoogle Scholar
- Tommerdahl M, Delemos KA, Whitsel BL, Favorov OV, Metz CB: The response of anterior parietal cortex to cutaneous flutter and vibration. J Neurophysiol. 1999, 82: 16-33.PubMedGoogle Scholar
- Favorov OV, Diamond ME: Demonstration of discrete place-defined columns – segregates – in the cat SI. Journal of Comparative Neurology. 1990, 298: 97-112. 10.1002/cne.902980108.View ArticlePubMedGoogle Scholar
- Sur M, Wall JT, Kaas JH: Modular distribution of neurons with slowly adapting and rapidly adapting responses in area 3b of somatosensory cortex in monkeys. J Neurophysiol. 1984, 51: 724-744.PubMedGoogle Scholar
- Tommerdahl M, Whitsel BL, Cox EG, Diamond ME, Kelly DG: Analysis of the periodicities in somatosensory cortical activity patterns. Society for Neuroscience Abstracts. 1987, 13: 470.Google Scholar
- Tommerdahl M, Favorov OV, Whitsel BL, Nakhle B, Gonchar YA: Minicolumnar activation patterns in cat and monkey SI cortex. Cerebral Cortex. 1993, 3: 399-411.View ArticlePubMedGoogle Scholar
- Tommerdahl M, Favorov O, Chiu J, Whitsel B: Optical intrinsic signal imaging of ipsilateral, contralateral, and bilateral forelimb inputs to cat SII. Society for Neuroscience Abstracts. 2004, : 642-612Google Scholar
- Buxhoeveden DP, Switala AE, Roy E, Casanova MF: Quantitative analysis of cell columns in the cerebral cortex. Journal of Neuroscience Methods. 2000, 97: 7-17. 10.1016/S0165-0270(99)00192-2.View ArticlePubMedGoogle Scholar
- Kohn A, Pinheiro A, Tommerdahl MA, Whitsel BL: Optical imaging in vitro provides evidence for the minicolumnar nature of cortical response. Neuroreport. 1997, 8: 3513-3518.View ArticlePubMedGoogle Scholar
- Simons SP, Tannan V, Chiu J, Favorov OV, Whitsel BL, Tommerdahl M: Amplitude-Dependent Response of SI Cortex to vibrotactile stimulation. Society for Neuroscience Abstracts. 2004, : 643-613Google Scholar
- Chen LM, Friedman RM, Roe Aw: Optical imaging of a tactile illusion in area 3b of the primary somatosensory cortex. Science. 2003, 302: 881-885. 10.1126/science.1087846.View ArticlePubMedGoogle Scholar
- Sheth BR, Moore CI, Sur M: Temporal modulation of spatial borders in rat barrel cortex. Journal of Neurophysiology. 1998, 79 (1): 464-470.PubMedGoogle Scholar
- Grinvald A, Frostig RD, Lieke EE, Hildescheim R: Optical imaging of neuronal activity. Physiol Reviews. 1988, 68: 1285-1365.Google Scholar
- Lieke EE, Frostig RD, Arieli A, Ts'o DY, Hildesheim R, Grinvald A: Optical imaging of cortical activity: real-time imaging using extrinsic dye-signals and high resolution imaging based on slow intrinsic signals. Annu Rev Physiol. 1989, 51: 543-559. 10.1146/annurev.ph.51.030189.002551.View ArticlePubMedGoogle Scholar
- Bonhoeffer T, Grinvald A: Optical imaging based on intrinsic signals: The methodology. Brain Mapping: The Methods Volume. Edited by: Toga AW, Mazziotia JC. 1996, Academic Press, Inc. New York, 55-97.Google Scholar
- Shmuel A, Grinvald A: Functional organization for direction of motion and its relationship to orientation maps in cat area 18. Journal of Neuroscience. 1996, 16: 6945-6964.PubMedGoogle Scholar
- Grinvald A, Shoham D, Glaser I, Vanzetta A, Shyoterman E, Slovin H, Wijnbergen C, Hildescheim RAA: In-Vivo optical imaging of cortical architecture and dynamics. Modern Techniques in Neuroscience Research. Edited by: Windhorst U, Johansson H. 1999, New York: Springer, 893-969.View ArticleGoogle Scholar
- Tommerdahl M, Delemos K, Vierck CJ, Favorov O, Whitsel B: Anterior parietal cortical response to tactile and skin-heating stimuli applied to the same skin site. Journal of Neurophysiology. 1996, 75: 2662-2670.PubMedGoogle Scholar
- Haglund M, Ojemann G, Blasdel G: Optical imaging of eliptiform and functional activity in human cerebral cortex. Nature. 1993, 358: 668-671. 10.1038/358668a0.View ArticleGoogle Scholar
- Ba A, Guiou M, Pouration N, Muthialu A, Rex D, Cannestra A, Chen J, Toga A: Multiwavelength Optical Intrinsic Signal Imaging of Cortical Spreading Depression. J Neurophysiol. 2002, 88: 2726-2735.View ArticlePubMedGoogle Scholar
- Cohen LB: Changes in neuron structure during action potential propagation and synaptic transmission. Physiol Reviews. 1973, 53: 373-418.Google Scholar
- MacVicar BA, Hochman D: Imaging of synaptically evoked intrinsic optical signals in hippocampal slices. Journal of Neuroscience. 1991, 11: 1458-1469.PubMedGoogle Scholar
- Woolsey TA, Rovainen CM, Cox SB, Henegar MH, Liang GE, Moskalenko YE, Sui J, Wei L: Neuronal units linked to microvascular modules in cerebral cortex: response elements for imaging the brain. Cereb Cortex. 1996, 6: 647-660.View ArticlePubMedGoogle Scholar
- Powell TPS, Mountcastle VB: Some aspects of the functional organization of the cortex of the postcentral gyrus of the monkey: A correlation of findings obtained in a single unit analysis with cytoarchitecture. Bulletin of the Johns Hopkins Hospital. 1959, 105: 133-162.PubMedGoogle Scholar
- Sretavan D, Dykes RW: The organization of two cutaneous submodalities in the forearm region of area 3b of cat somatosensory cortex. Journal of Comparative Neurology. 1983, 213: 381-398. 10.1002/cne.902130403.View ArticlePubMedGoogle Scholar
- Bruno RM, Khatri VL, Land PW, Simons DJ: Thalamocortical angular tuning domains within individual barrels of rat somatosensory cortex. Journal of Neuroscience. 2003, 23: 9565-9574.PubMedGoogle Scholar
- Hess A, Stiller D, Kaulisch T, Heil P, Scheich H: New insights into the hemodynamic blood oxygenation level-dependent response through combination of functional magnetic resonance imaging and optical recording in gerbil barrel cortex. Journal of Neuroscience. 2000, 20: 3328-3338.PubMedGoogle Scholar
- Fujibayashi T, Sugiura M, Yanagimoto M, Harada J, Goto Y: Brain energy metabolism and blood flow during sevoflurane and halothane anesthesia: Effects of hypocapnia and blood pressure fluctuations. Acta Anaesthesiol Scand. 1994, 38: 413-418.View ArticlePubMedGoogle Scholar
- Burdett NG, Menon DK, Carpenter TA, Jones JG, Hall LD: Visualization of changes in regional cerebral blood flow (rCBF) produced by ketamine using long TE gradient-echo sequences: Preliminary results. Magnetic Resonance Imaging. 1995, 13: 549-553. 10.1016/0730-725X(95)00010-E.View ArticlePubMedGoogle Scholar
- Chubbuck JG: Small-motion biological stimulator. APL Technical Digest. 1966, May-Jun: 18-23.Google Scholar
- Tommerdahl M, Whitsel B, Favorov O, Metz C, BL O'Quinn: Responses of contralateral SI and SII in cat to same site cutaneous flutter versus vibration. Journal of Neurophysiology. 1999, 82: 1982-1992.PubMedGoogle Scholar
- Grinvald A: Real-time optical mapping of neuronal activity: from single growth cones to the intact mammalian brain. Annual Review of Neuroscience. 1985, 8: 263-305. 10.1146/annurev.ne.08.030185.001403.View ArticlePubMedGoogle Scholar
- Grinvald A, Bonhoeffer T, Malonek D, Shoham D, Bartfeld E, Arierli A, Hildesheim R, Ratzlaff E: Optical imaging of architecture and function in the living brain. Memory Organization and Locus of Change. Edited by: Squire L, Weinberger N, Lynch G, McGaugh JNY. 1991, Oxford Univ. Press, 49-85.Google Scholar
- Grinvald A, Lieke E, Frostig R, Hildesheim R: Cortical point-spread function and long-range lateral interactions revealed by real-time optical imaging of macaque monkey primary visual cortex. Journal of Neuroscience. 1994, 14: 2545-2568.PubMedGoogle Scholar
- Ebner T, Chen G: Use of voltage-sensitive dyes and optical recordings in the central nervous system. Progress in Neurobiology. 1995, 46: 463-506. 10.1016/0301-0082(95)00010-S.View ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.