Abstract

Hyperspectral interferometric microscopy uses a unique combination of optics and algorithm design to extract information. Local brain activity rapidly changes local blood flow and red blood cell concentration (absorption) and oxygenation (color). We demonstrate that brain activity evoked during whisker stimulation can be detected with hyperspectral interferometric microscopy to identify the active whisker–barrel cortex in the rat brain. Information about constituent components is extracted across the entire spectral band. Algorithms can be flexibly optimized to discover, detect, quantify, and visualize a wide range of significant biological events, including changes relevant to the diagnosis and treatment of disease.

© 2006 Optical Society of America

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2004 (2)

F. N. Joudi and B. R. Konety, "Fluorescence cystoscopy and bladder surveillance," Curr. Opin. Urol. 14, 265-270 (2004).
[CrossRef] [PubMed]

D. R. Fuhrmann, C. Preza, J. A. O'Sullivan, D. L. Snyder, and W. H. Smith, "Spectrum estimation from quantum-limited interferograms," IEEE Trans. Signal Process. 52, 950-961 (2004).
[CrossRef]

2003 (7)

G. A. Swayze, R. N. Clark, A. F. H. Goetz, T. G. Chrien, and N. S. Gorelick, "Effects of spectrometer band pass, sampling, and signal-to-noise ratio on spectral identification using the Tetracorder algorithm," J. Geophys. Res. 108(E9), 5105, doi: (2003).
[CrossRef]

A. K. Dunn, A. Devor, H. Bolay, M. L. Andermann, M. A. Moskowitz, A. M. Dale, and D. A. Boas, "Simultaneous imaging of total cerebral hemoglobin concentration, oxygenation, and blood flow during functional activation," Opt. Lett. 28, 28-30 (2003).
[CrossRef] [PubMed]

N. Pouratian, S. A. Sheth, N. A. Martin, and A. W. Toga, "Shedding light on brain mapping: advances in human optical imaging," Trends Neurosci. 26, 277-282 (2003).
[CrossRef] [PubMed]

M. E. Raichle, "Functional brain imaging and human brain function," J. Neurosci. 23, 3959-3962 (2003).
[PubMed]

N. K. Logothetis, "The underpinnings of the BOLD functional magnetic resonance imaging signal," J. Neurosci. 23, 3963-3971 (2003).
[PubMed]

A. Devor, A. K. Dunn, M. L. Andermann, I. Ulbert, D. A. Boas, and A. M. Dale, "Coupling of total hemoglobin concentration, oxygenation, and neural activity in rat somatosensory cortex," Neuron 39, 353-359 (2003).
[CrossRef] [PubMed]

D. R. Fuhrmann and W. H. Smith, "Empirical modeling and calibration of Fourier transform spectrometers I: linearization and normalization of interferograms," Opt. Eng. 42, 2268-2276 (2003).
[CrossRef]

2002 (1)

J. Erinjeri and T. A. Woolsey, "Spatial integration of vascular changes with neural activity in mouse cortex," J. Cereb. Blood Flow Metab. 22, 353-360 (2002).
[CrossRef] [PubMed]

2001 (2)

P. D. Hammer, L. F. Johnson, A. W. Strawa, S. E. Dunagan, R. G. Higgins, J. A. Brass, R. E. Slye, D. V. Sullivan, W. H. Smith, B. M. Lobitz, and D. L. Peterson, "Surface reflectance mapping using interferometric spectral imagery from a remotely piloted aircraft," IEEE Trans. Geosci. Remote Sens. 39, 2499-2506 (2001).
[CrossRef]

J. Niamtu, "Digitally processed ultraviolet images: a convenient, affordable, reproducible means of illustrating ultraviolet clinical examination," Dermatol. Surg. 27, 1039-1042 (2001).
[CrossRef]

2000 (1)

L. Hubert, J. Meulman, and W. Heiser, "Two purposes for matrix factorization: a historic appraisal," SIAM Review 42, 68-82 (2000).
[CrossRef]

1999 (2)

P. Asawanonda and C. R. Taylor, "Wood's light in dermatology," Int. J. Dermatol 38, 801-807 (1999).
[CrossRef] [PubMed]

S. S. Kety, "Circulation and metabolism of the human brain," Brain Res. Bull. 50, 415-416 (1999).
[CrossRef]

1998 (1)

J. A. O'Sullivan, R. E. Blahut, and D. L. Snyder, "Information theoretic image formation," IEEE Trans. Inf. Theory 44, 2094-2123 (1998).
[CrossRef]

1997 (1)

C. J. Hodge, Jr., R. T. Stevens, H. Newman, J. Merola, and C. Chu, "Identification of functioning cortex using cortical optical imaging," Neurosurgery 41, 1137-1144 (1997).
[CrossRef] [PubMed]

1996 (2)

D. Malonek and A. Grinvald, "Interactions between electrical activity and cortical microcirculation revealed by imaging spectroscopy: implications for functional brain mapping," Science 272, 551-554 (1996).
[CrossRef] [PubMed]

J. L. Dowling, M. M. Henegar, D. Liu, C. M. Rovainen, and T. A. Woolsey, "Rapid optical imaging of whisker responses in the rat barrel cortex," J. Neurosci. Methods 66, 113-122 (1996).
[CrossRef] [PubMed]

1993 (1)

S. B. Cox, T. A. Woolsey, and C. M. Rovainen, "Localized dynamic changes in cortical blood flow with whisker stimulation corresponds to matched vascular and neuronal architecture of rat barrels," J. Cereb. Blood Flow Metab. 13, 899-913 (1993).
[CrossRef] [PubMed]

1992 (4)

D. L. Snyder, T. J. Schulz, and J. A. O'Sullivan, "Deblurring subject to nonnegativity constraints," IEEE Trans. Signal Proces. 40, 1143-1150 (1992).
[CrossRef]

D. J. Simons, G. E. Carvell, A. E. Hershey, and D. P. Bryant, "Responses of barrel cortex neurons in awake rats and effects of urethane anesthesia," Exp. Brain Res. 91, 259-272 (1992).
[CrossRef] [PubMed]

P. D. Hammer, F. P. J. Valero, D. L. Peterson, and W. H. Smith, "Remote sensing of Earth's atmosphere and surface using a digital array scanned interferometer: a new type of imaging spectrometer," J. Imaging Sci. Technol. 36, 417-422 (1992).

M. M. Haglund, G. A. Ojemann, and D. W. Hochman, "Optical imaging of epileptiform and functional activity in human cerebral cortex," Nature 358, 668-671 (1992).
[CrossRef] [PubMed]

1991 (4)

W. H. Smith and W. Schempp, "Digital array scanned interferometers," Exp. Astron. 1, 389-405 (1991).
[CrossRef]

M. Ehlers, "Multisensor image fusion techniques in remote sensing," J. Photogramm. Remote Sens. 46, 19-30 (1991).
[CrossRef]

W. G. Zijlstra, A. Buursma, and W. P. Meeuwsen-van der Roest, "Absorption spectra of human fetal and adult oxyhemoglobin, de-oxyhemoglobin, carboxyhemoglobin, and methemoglobin," Clin. Chem. 37, 1633-1638 (1991).
[PubMed]

I. Csiszár, "Why least squares and maximum entropy? An axiomatic approach to inference for linear inverse problems," Ann. Stat. 19, 2032-2066 (1991).
[CrossRef]

1990 (1)

S. Ogawa, T. M. Lee, A. R. Kay, and D. W. Tank, "Brain magnetic resonance imaging with contrast dependent on blood oxygenation," Proc. Natl. Acad. Sci. U.S.A. 87, 9868-9872 (1990).
[CrossRef] [PubMed]

1989 (1)

G. Ojemann, J. Ojemann, E. Lettich, and M. Berger, "Cortical language localization inleft, dominant hemisphere. An electrical stimulation mapping investigation in 117 patients," J. Neurosurg. 71, 316-326 (1989).
[CrossRef] [PubMed]

1986 (2)

A. Grinvald, E. Lieke, R. D. Frostig, C. D. Gilbert, and T. N. Wiesel, "Functional architecture of cortex revealed by optical imaging of intrinsic signals," Nature 324, 361-364 (1986).
[CrossRef] [PubMed]

G. G. Blasdel and S. G, "Voltage-sensitive dyes reveal a modular organization in monkey striate cortex," Nature 321, 579-585 (1986).
[CrossRef] [PubMed]

1979 (1)

M. Wong-Riley, "Changes in the visual system of monocularly sutured or enucleated cats demonstrable with cytochrome oxidase histochemistry," Brain Res. 171, 11-28 (1979).
[CrossRef] [PubMed]

1974 (1)

C. Welker and T. A. Woolsey, "Structure of layer IV in the somatosensory neocortex of the rat: description and comparison with mouse," J. Comp. Neurol. 158, 437-454 (1974).
[CrossRef] [PubMed]

1970 (1)

T. A. Woolsey and H. Van der Loos, "The structural organization of layer IV in the somatosensory region (SI) of mouse cerebral cortex: the description of a cortical field composed of discrete cytoarchitectonic units," Brain Res. 17, 205-242 (1970).
[CrossRef] [PubMed]

1966 (1)

M. M. Ter-Pogossian and H. N. Wagner, Jr., "A new look at the cyclotron for making short-lived isotopes," Nucleonics 24, 50-62 (1966).

1963 (1)

R. S. Ross, "Clinical applications of coronary arteriography," Circulation 27, 107-112 (1963).

1959 (1)

F. M. Sones, Jr., E. K. Shirey, W. L. Proudfit, and R. N. Westcaott, "Cine-coronary arteriography," Circulation 20, 773 (1959).

1937 (1)

W. Penfield, "The circulation of the epileptic brain," Res. Publ. Assoc. Res. Nerv. Ment. Dis. 18, 605-637 (1937).

1924 (1)

E. A. Graham, W. H. Cole, and G. H. Copher, "Visualization of the gallbladder by the sodium salt of tetrabromophenophthalien.," JAMA , J. Am. Med. Assoc. 82, 1777-1778 (1924).
[CrossRef]

1870 (1)

G. Fritsch and E. Hitzig, "Über die elektrische Erregbarkheit des Grosshirns," Arch. Anat. Physiol. wissen. Med. 37, 300-332 (1870).

Andermann, M. L.

A. Devor, A. K. Dunn, M. L. Andermann, I. Ulbert, D. A. Boas, and A. M. Dale, "Coupling of total hemoglobin concentration, oxygenation, and neural activity in rat somatosensory cortex," Neuron 39, 353-359 (2003).
[CrossRef] [PubMed]

A. K. Dunn, A. Devor, H. Bolay, M. L. Andermann, M. A. Moskowitz, A. M. Dale, and D. A. Boas, "Simultaneous imaging of total cerebral hemoglobin concentration, oxygenation, and blood flow during functional activation," Opt. Lett. 28, 28-30 (2003).
[CrossRef] [PubMed]

Asawanonda, P.

P. Asawanonda and C. R. Taylor, "Wood's light in dermatology," Int. J. Dermatol 38, 801-807 (1999).
[CrossRef] [PubMed]

Berger, M.

G. Ojemann, J. Ojemann, E. Lettich, and M. Berger, "Cortical language localization inleft, dominant hemisphere. An electrical stimulation mapping investigation in 117 patients," J. Neurosurg. 71, 316-326 (1989).
[CrossRef] [PubMed]

Blahut, R. E.

J. A. O'Sullivan, R. E. Blahut, and D. L. Snyder, "Information theoretic image formation," IEEE Trans. Inf. Theory 44, 2094-2123 (1998).
[CrossRef]

J. A. O'Sullivan, R. E. Blahut, and D. L. Snyder, "Information theoretic image formation," in Information Theory: 50 Years of Discovery, S.Verdú and S.W.McLaughlin, eds. (IEEE, 2000), pp. 50-79.

Blasdel, G. G.

G. G. Blasdel and S. G, "Voltage-sensitive dyes reveal a modular organization in monkey striate cortex," Nature 321, 579-585 (1986).
[CrossRef] [PubMed]

Boas, D. A.

A. Devor, A. K. Dunn, M. L. Andermann, I. Ulbert, D. A. Boas, and A. M. Dale, "Coupling of total hemoglobin concentration, oxygenation, and neural activity in rat somatosensory cortex," Neuron 39, 353-359 (2003).
[CrossRef] [PubMed]

A. K. Dunn, A. Devor, H. Bolay, M. L. Andermann, M. A. Moskowitz, A. M. Dale, and D. A. Boas, "Simultaneous imaging of total cerebral hemoglobin concentration, oxygenation, and blood flow during functional activation," Opt. Lett. 28, 28-30 (2003).
[CrossRef] [PubMed]

Bolay, H.

Brass, J. A.

P. D. Hammer, L. F. Johnson, A. W. Strawa, S. E. Dunagan, R. G. Higgins, J. A. Brass, R. E. Slye, D. V. Sullivan, W. H. Smith, B. M. Lobitz, and D. L. Peterson, "Surface reflectance mapping using interferometric spectral imagery from a remotely piloted aircraft," IEEE Trans. Geosci. Remote Sens. 39, 2499-2506 (2001).
[CrossRef]

Bryant, D. P.

D. J. Simons, G. E. Carvell, A. E. Hershey, and D. P. Bryant, "Responses of barrel cortex neurons in awake rats and effects of urethane anesthesia," Exp. Brain Res. 91, 259-272 (1992).
[CrossRef] [PubMed]

Buursma, A.

W. G. Zijlstra, A. Buursma, and W. P. Meeuwsen-van der Roest, "Absorption spectra of human fetal and adult oxyhemoglobin, de-oxyhemoglobin, carboxyhemoglobin, and methemoglobin," Clin. Chem. 37, 1633-1638 (1991).
[PubMed]

Carvell, G. E.

D. J. Simons, G. E. Carvell, A. E. Hershey, and D. P. Bryant, "Responses of barrel cortex neurons in awake rats and effects of urethane anesthesia," Exp. Brain Res. 91, 259-272 (1992).
[CrossRef] [PubMed]

Chrien, T. G.

G. A. Swayze, R. N. Clark, A. F. H. Goetz, T. G. Chrien, and N. S. Gorelick, "Effects of spectrometer band pass, sampling, and signal-to-noise ratio on spectral identification using the Tetracorder algorithm," J. Geophys. Res. 108(E9), 5105, doi: (2003).
[CrossRef]

Chu, C.

C. J. Hodge, Jr., R. T. Stevens, H. Newman, J. Merola, and C. Chu, "Identification of functioning cortex using cortical optical imaging," Neurosurgery 41, 1137-1144 (1997).
[CrossRef] [PubMed]

Clark, R. N.

G. A. Swayze, R. N. Clark, A. F. H. Goetz, T. G. Chrien, and N. S. Gorelick, "Effects of spectrometer band pass, sampling, and signal-to-noise ratio on spectral identification using the Tetracorder algorithm," J. Geophys. Res. 108(E9), 5105, doi: (2003).
[CrossRef]

Cole, W. H.

E. A. Graham, W. H. Cole, and G. H. Copher, "Visualization of the gallbladder by the sodium salt of tetrabromophenophthalien.," JAMA , J. Am. Med. Assoc. 82, 1777-1778 (1924).
[CrossRef]

Copher, G. H.

E. A. Graham, W. H. Cole, and G. H. Copher, "Visualization of the gallbladder by the sodium salt of tetrabromophenophthalien.," JAMA , J. Am. Med. Assoc. 82, 1777-1778 (1924).
[CrossRef]

Cox, S. B.

S. B. Cox, T. A. Woolsey, and C. M. Rovainen, "Localized dynamic changes in cortical blood flow with whisker stimulation corresponds to matched vascular and neuronal architecture of rat barrels," J. Cereb. Blood Flow Metab. 13, 899-913 (1993).
[CrossRef] [PubMed]

Csiszár, I.

I. Csiszár, "Why least squares and maximum entropy? An axiomatic approach to inference for linear inverse problems," Ann. Stat. 19, 2032-2066 (1991).
[CrossRef]

Dale, A. M.

A. Devor, A. K. Dunn, M. L. Andermann, I. Ulbert, D. A. Boas, and A. M. Dale, "Coupling of total hemoglobin concentration, oxygenation, and neural activity in rat somatosensory cortex," Neuron 39, 353-359 (2003).
[CrossRef] [PubMed]

A. K. Dunn, A. Devor, H. Bolay, M. L. Andermann, M. A. Moskowitz, A. M. Dale, and D. A. Boas, "Simultaneous imaging of total cerebral hemoglobin concentration, oxygenation, and blood flow during functional activation," Opt. Lett. 28, 28-30 (2003).
[CrossRef] [PubMed]

Deerwester, S.

G. W. Fumas, S. Deerwester, S. T. Dumias, T. K. Landauer, R. A. Harshman, L. A. Streeter, and K. E. Lochbaum, "Information retrieval using a singular value decomposition model of latent semantic structure," in Proceedings of the Eleventh Annual International Conference on Research and Development in Information Retrieval (ACM Press, 1988), pp. 465-480.

Devor, A.

A. Devor, A. K. Dunn, M. L. Andermann, I. Ulbert, D. A. Boas, and A. M. Dale, "Coupling of total hemoglobin concentration, oxygenation, and neural activity in rat somatosensory cortex," Neuron 39, 353-359 (2003).
[CrossRef] [PubMed]

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Figures (4)

Fig. 1
Fig. 1

(a) Photograph of the dissecting microscope with a CCD camera for standard video capture to the upper left and the hyperspectral interferometric microscopy sensor (DASI, the black attachment) to the upper right. (b) Schematic showing the optical, stimulating, recording, and analysis paths for the standard IOS recordings and for DASI capture. Video paths are directed to one or the other sensor by the beam splitter in the dissecting microscope. The entire apparatus is mounted on a Diagnostic Instruments (Sterling Heights) SMS20 boom stand microscope base. For image capture with the DASI, this was moved in 3 μm increments with a stepper motor. The drawing shows a rat with its head under the objective. The brain surface is viewed through the thinned skull that is covered with mineral oil and a coverslip. The brain is illuminated with focused white or passband filtered light. For video recordings, images are digitized and saved to a computer and can be analyzed within several minutes. For hyperspectral interferometry, the computer controls the stepper motor and data collection; images are processed off line. Physiological parameters (e.g., blood pressure and electrocardiogram are not shown) are recorded in the computer. The stimulator and programmed stimulus sequences are under computer control (WPI Pro4).

Fig. 2
Fig. 2

(a) Linear, normalized absorption spectra (arbitrary linear scale) for oxyhemoglobin (HbO2) and deoxyhemoglobin (Hbr) in solution[11] and smoothed filter passbands. For shorter wavelengths (green filter, 540 ± 12.5 nm), the Hbt absorption is at least 5 times greater than that for longer wavelengths (orange filter, 620 ± 30 nm). The green filter includes an isobestic point of the hemoglobin absorption spectra and is roughly equally sensitive to Hbr and HbO2 (46% and 54%, respectively). The orange filter is ∼4 times as sensitive to Hbr as to HbO2 (78% and 22%, respectively). (Filter passbands are indicated in all panels.) (b) Relative spectral reflectance computed from data captured by DASI at baseline or rest. (c) Relative spectral reflectance with whisker activation computed from data captured by DASI. (d) Relative differences in the spectra shown in (b) and (c). While changes occur in the regions selected by the filter passbands, additional information is available from regions not passed by the filters. The dashed line indicates that there is no difference in reflectance between background and active images. (e) Components of the reflection spectra extracted from data captured by DASI. The three most significant spectral components extracted by end-member analysis are likely reflection related to water H2O, HbO2, and Hbr. The HbO2 and Hbr curves are roughly the inverse of the corresponding spectra in (a).

Fig. 3
Fig. 3

(a) Drawing of a rat with the surface of the whisker cortex shown through the thinned skull. When the right whiskers move, the left cortex is activated. (b) Sketch of the rat brain viewed from above, showing the main artery (middle cerebral) that supplies the whisker representation on the right cerebral hemisphere only (top). The outline of the rat's body map (anatomical and functional) is drawn on a photograph of a histological section stained for the activity of the mitochondrial enzyme CO as scaled and placed over the left hemisphere (bottom). The image extends beyond the brain outline because it represents a view that unwraps the curved cortical surface. Patches of nerve cells (barrels) define regions of inputs from the whiskers on the opposite face. The arrow points toward the nose (a = anterior). (c) Composite stack of histological sections (stained for activity of the mitochondrial enzyme CO), including the brain surface used to align vessels (arteries, a; veins, v) visualized during video recording with tissue markers found 500 μm under the surface. The box here and in (d) and (e) indicates the location of the images in Fig. 4. (d) Dark-staining CO patches show the location of the representations of different whiskers on the opposite face. (e) Individual barrels are circled to show the match with different images displayed in Fig. 4. Compass: a, anterior (nose); m, medial (toward the midline) gives the orientation for (c)–(e).

Fig. 4
Fig. 4

Imaging Results. The surface of the left hemisphere of the rat brain visualized through the thinned skull. Arteries (a) and veins (v) on the brain surface and in the covering membrane (in the dura mater, d) are prominent. Images are arranged in two functional groups (Baseline and Active Baseline) by the three different imaging modalities (Optically Filtered, Digitally Filtered, and Component Analysis) and by the spectra used (Green and Orange). Optically filtered images were collected with illumination through green and orange filters. Digitally filtered images were processed with software filters designed to mimic the optical filters applied to hyperspectral data [Fig. (2a)]. Component analysis images were based on spectral signatures of major components [Fig. (2e)]. For each image the anatomical regions defining the whisker representations in the histological sections (Fig. 3) are outlined. The baseline (at-rest) images are remarkably similar for all three approaches. With whisker stimulation the strong changes in the optically filtered images are partially suggested in the digitally filtered and component analysis images. See text for details and consideration of similarities and differences among the three different methods of emphasizing image components. Compass: m, medial; a, anterior.

Equations (10)

Equations on this page are rendered with MathJax. Learn more.

S ( m , n , k ) , 1 m M , 1 n N , 1 k K ,
A ( m , n , k ) = l = 1 L u ( m , n , l ) d ( l ) v ( k , l )
I ( S A ) = m = 1 M n = 1 N m = 1 K [ S ( m , n , k ) ln S ( m , n , k ) A ( m , n , k ) S ( m , n , k ) + A ( m , n , k ) ] .
I ( S A ) = m = 1 M n = 1 N k = 1 K [ S ( m , n , k ) ln S ( m , n , k ) l = 1 L u ( m , n , l ) d ( l ) v ( k , l ) S ( m , n , k ) + l = 1 L u ( m , n , l ) d ( l ) v ( k , l ) ] = min Φ m = 1 M n = 1 N k = 1 K l = 1 L [ Φ ( l | m , n , k ) S ( m , n , k ) ln Φ ( l | m , n , k ) S ( m , n , k ) u ( m , n , l ) d ( l ) v ( k , l ) Φ ( l | m , n , k ) S ( m , n , k ) + u ( m , n , l ) d ( l ) v ( k , l ) ] .
A ( m , n , k ) = l = 1 L u ( m , n , l ) d ( l ) v ( k , l ) .
= { Φ : Φ ( l | m , n , k ) 0 , l = 1 L Φ ( l | m , n , k ) = 1 }
Φ j ( l | m , n , k ) = u ( j ) ( m , n , l ) d ( j ) ( l ) v ( j ) ( k , l ) l = 1 L u ( j ) ( m , n , l ) d ( j ) ( l ) v ( j ) ( k , l ) ,
d ( j + 1 ) ( l ) = m = 1 M n = 1 N k = 1 K Φ ( j ) ( l | m , n , k ) S ( m , n , k ) ,
v ( j + 1 ) ( k , l ) = 1 d ( j + 1 ) ( l ) m = 1 M n = 1 N Φ ( j ) ( l | m , n , k ) S ( m , n , k ) ,
u ( j + 1 ) ( m , n , l ) = 1 d ( j + 1 ) ( l ) k = 1 K Φ ( j ) ( l | m , n , k ) S ( m , n , k ) .

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