2.1.

Light Sources

We compared three light sources (LED, SLD, and LD) in vitro and two sources (LED, LD) in vivo. The LED ( $660\mathrm{nm}$ , rated at $3.5\mathrm{mcd}$ or $1.6\mathrm{mW}$ , B5b-436-30, Roithner Lasertechnik GmbH, Vienna, Austria) and SLD ( $833\mathrm{nm}$ , $9\mathrm{mW}$ , Superlum Diodes Ltd., Moscow, Russia) were operated in free space. The LD ( $660\mathrm{nm}$ , $5\mathrm{mW}$ , D660-5, US-Lasers, Inc., Baldwin Park, California) was coupled to a $1\text{-}\mathrm{mm}$ -diameter fiber optic. The LD and SLD were temperature-regulated by feedback-controlled thermoelectric coolers. The LED and LD were driven with batteries at a constant voltage, and the SLD was powered with a current-regulated power supply (Superlum Pilot 4, Superlum Diodes Ltd., Moscow, Russia). While current-regulated supplies are generally preferred for both LEDs and LDs due to very slow temperature and drift effects, we found no difference between the two methods in our root mean square (RMS) noise levels.

2.2.

In Vitro: Crustacean Nerve

We extracted nerves from the first two most rostral walking legs of lobsters (Homarus americanus) using the Furusawa “pulling out” method²⁰ and tied the ends with silk sutures to prevent axoplasmic leakage. Our invertebrate recording technique was reported earlier.²¹ Briefly, we placed each isolated nerve in a recording chamber flooded with marine crustacean solution (in mM: 525 NaCl, 13.3 KCl, 12.4 $\mathrm{Ca}{\mathrm{Cl}}_2$ , 24.8 $\mathrm{Mg}{\mathrm{Cl}}_2$ , 5.0 dextrose, to pH 7.0 with $\mathrm{Na}\mathrm{H}\mathrm{C}{\mathrm{O}}_3$ ). The chamber featured a central, rectangular well with four smaller wells on either side. Each well was fitted with a silver electrode and isolated with petroleum jelly. A set of electrodes on one side of the imaging window delivered current pulse stimuli [STIM in Fig. 1a ], and a second set of electrodes (EP) recorded the electrical response after the population action potentials passed through the center optical well. The bottom of the central well contained a narrow slit covered with a microscope slide through which the light was transmitted during optical recordings. Light from an LED, SLD, or LD light source [LS in Fig. 1a] passed through a polarizer (POL1; for LED and LD: VIS $4\mathrm{K}$ , Linos Photonics, Milford, Massachusetts; for SLD: Polarcor 05P109AR.16, Newport Corp., Irvine, California) oriented at $45\mathrm{deg}$ with respect to the long axis of the nerve bundle. Transmitted light passed through a second polarizer (POL2) crossed $90\mathrm{deg}$ with respect to the first. The birefringent light intensity was recorded with a photodiode (PD) positioned over the second polarizer. The apparatus was constructed on an antivibration floating table (Minus K, Inglewood, California) to minimize mechanical noise contributions. During neural tissue measurements, all light sources were driven to produce an initial output power between 1 and $3\mathrm{mW}$ .

Fig. 1

Schematics of (a) in vitro, and (b) in vivo optical recording paradigms. For the in vitro paradigm (a), we stimulated lobster nerves with short-current pulses (STIM), and the resulting field potential was recorded on the other side of the window (EP). Light from an LED, SLD, or LD (LS) was transmitted through the recording chamber between crossed polarizers (POL1, POL2). The transmitted intensity was recorded with a photodiode (PD). For the in vivo paradigm (b), epidural electrodes (LEEG, MEEG) recorded the electrical evoked responses after whisker twitch stimuli; an LED or LD (LS), and a photodiode (PD) implanted over the barrel cortex, recorded the optical responses.

Each nerve was stimulated with $0.2\text{-}\mathrm{ms}$ current pulses $(\sim 2\mathrm{mA})$ at random intervals between one and two seconds ( $0.67\text{-}\mathrm{Hz}$ average stimulation rate) using a direct current isolated stimulator (Model A365R, World Precision Instruments, Inc., Sarasota, Florida). Electrical responses were recorded with a differential amplifier (Linear Technology LT1167) and filtered between $0.1\mathrm{Hz}$ and $3.2\mathrm{kHz}$ , with x1000 gain. Optical signals were filtered $\left(0.1\mathrm{Hz}\text{to}3.2\mathrm{kHz}\right)$ , amplified with a $\times 1000$ gain, and digitized simultaneously with the electrical signals at $20\mathrm{kHz}$ per channel. We averaged data across 1000 stimuli using three nerves for each light source.

2.3.

In Vivo: Rat Barrel Cortex

Sprague-Dawley and Long-Evans female rats ( $250\text{to}300\mathrm{g}$ , Taconic, $n=3$ ) were anesthetized with $100\mathrm{mg}∕\mathrm{kg}$ ketamine and $10\mathrm{mg}∕\mathrm{kg}$ xylazine and placed in a stereotaxic frame. All animal procedures were approved by the Washington State University Animal Care and Use Committee. We continuously monitored electrocardiogram signals from subcutaneous pin electrodes. Stainless steel screw electroencephalogram (EEG) electrodes entered holes drilled $4\mathrm{mm}$ posterior to bregma [B in Fig. 1b], $3\mathrm{mm}$ medial (MEEG), and $1\mathrm{mm}$ lateral (LEEG) of the right temporal ridge (TR). The EEG ground reference hole (GND) was drilled $2\mathrm{mm}$ caudal to lambda and $3\mathrm{mm}$ to the right of the midline. The photodiode was coupled to a $1\text{-}\mathrm{mm}$ -diameter, $8\text{-}\mathrm{mm}$ -long piece of plastic fiber optic. The free end of the photodiode fiber was inserted into a $1.5\text{-}\mathrm{mm}$ -diameter hole (PD) positioned $2\mathrm{mm}$ caudal to bregma medial to the right temporal ridge, applying light pressure to the dura to reduce the cardiac artifact. LED and LD illumination were directed into another $1.5\text{-}\mathrm{mm}$ -diameter hole (LS) placed $2\mathrm{mm}$ caudal of the photodiode hole. The dura was left intact beneath all holes.

We twitched a group of whiskers (C0, C1, C2, D0, and D1) on the side contralateral to the EEG and optical detectors with a burst (5 twitches at $10\mathrm{Hz}$ ) of $2\text{-}\mathrm{ms}$ , $1\text{-}\mathrm{mm}$ upward deflections. Stimuli, auditory controls, and sham controls were randomly interleaved at $7.5\text{-}\text{second}$ intervals. Optical (AC photodiode $\times 500$ , DC photodiode $\times 1$ ), LEEG, MEEG, and EKG signals were filtered $\left(0.1\mathrm{Hz}\text{to}3.2\mathrm{kHz}\right)$ and digitized at $20\mathrm{kHz}$ . We averaged across 200 stimuli (plus equal numbers of auditory and sham trials) with LED and LD light sources, then euthanized the rat with a lethal dose of sodium pentabarbitol. We filtered the cardiac arfifact offline by finding the average optical response per heart beat and subtracting the average cardiac waveform from the optical data at every cardiac trigger point in the data set.^{12, 22}

2.4.

Instrument Noise Measurement

We assessed the noise contributions from the light sources and photodiodes by illuminating the photodiode with each light source (LED, LD, and SLD) in turn, and calculating the RMS of signals collected at $20\mathrm{kHz}$ for $200\text{seconds}$ , varying the intensity of the light sources in steps. We plotted the RMS [Eq. 1] noise at each intensity against the radiant flux through the photodiode ( $68{\mathrm{mm}}^2$ , UDT-555UV/LN, UDT Sensors, Hawthorne, California). For a collection of $n$ samples $\{x_1,x_2,\dots ,x_n\}$ ,

Noise contributions from the photodiode and amplifier were calculated to be $5.67\mu \mathrm{V}$ , which included photodiode dark current noise, amplifier input noise, and Johnson noise in the resistors. Table 1 outlines the contributions of the photodiode, amplifiers, and resistors for a $500\text{-}\mathrm{Hz}$ bandwidth; the complete photodiode/amplifier circuit is described in Ref. 21. Since these noises are uncorrelated, their contributions add in quadrature to form the total instrument noise. Thus, we expect the measured RMS of the dark signal noise to fall close to the anticipated value, $5.67\mu \mathrm{V}$ , calculated from the component specifications.

Table 1

Noise contributions of the photodiode dark current, the integrated op-amp input noise, the free op-amp input noise, and Johnson noise from the feedback resistors. The addition of the noises in quadrature predicts the total instrument noise, 5.67μV . After instrument noise, the RMS noise contributions of illumination and physiological sources are tabulated in vitro (lobster) and in vivo (rat) and compared to the peak amplitudes of the stimulus-evoked optical changes. The standard errors for these measurements are large due to the variability of signal strength and illumination intensity from trial to trial, but values give the reader a general idea of each source’s noise generation.

The photodiode readings were calibrated and compared with an optical power meter (OPM, console PM100, head S130A, Thorlabs GmbH, Karlsfeld, Germany). We correlated the amplifier output ( $V_{\mathrm{out}}$ , volts) with radiant flux ( $e$ , watts) measured with the OPM and found the following linear fit:

2.5.

Physiological Noise Assessment

For each experiment, in vitro and in vivo, $450\text{seconds}$ of optical data were recorded in the absence of stimulation. We partitioned each data set into $150\text{-}\text{seconds}$ epochs, applied a second-order Butterworth filter from $0.05\text{to}20\mathrm{Hz}$ , and subsampled down from $20\mathrm{kHz}\text{to}100\mathrm{Hz}$ . A fast Fourier transform (FFT) of the $100\text{-}\mathrm{Hz}$ data was used to assess the frequency characteristics of slow physiological noise sources. The FFTs were compared across light sources, and in living and dead tissue.

2.6.

Stimulus-Evoked SNR

For both in vitro and in vivo paradigms, we compared the RMS noise and SNRs [Eq. 4] of the optical signal across light sources:

3.1.

Source-Detector Noise

RMS noise increased linearly with intensity for the LED and SLD sources [Fig. 2a ]. The LD noise increased with the LED and SLD noise at low intensities, but increased sharply at $0.5\mathrm{mW}$ to a noise level exceeding those of the LED and SLD by a factor of 5 or greater [Fig. 2a].

Fig. 2

Relationship between noise (RMS) and radiant flux (RF). (a) RMS against RF for three sources: LED, SLD, and LD. The upper limits for LED, SLD, and LD RMS in the illustrated range are 0.27, 1.14, and $5.67\mathrm{nW}$ , respectively. (b) RMS normalized to the radiant intensity. The laser’s sharp increase in RMS at $0.5\mathrm{mW}$ reflects noise introduced as the LD transitioned from LED mode to lasing.

We divided RMS noise by radiant flux (RF) to account for the effects of differing intensities on RMS. Figure 2b shows the data from Fig. 2a normalized to the RF and measured using the $68\text{-}{\mathrm{mm}}^2$ photodiode. All three sources showed a rapid decrease in RMS/RF between 0 and $0.25\mathrm{mW}$ . At $0.5\mathrm{mW}$ , the LD RMS/RF increased sharply in the transition to lasing. Above $0.75\mathrm{mW}$ of RF, the RMS/RF of all three light sources decreased [Fig. 2b].

3.2.

Instrument Dark Noise

In the absence of light, we measured a total of $4.53\text{-}\mu \mathrm{V}$ RMS noise from the photodiode and amplifier (Fig. 3 ), slightly lower than the predicted value, $5.67\mu \mathrm{V}$ (Table 1).

Fig. 3

Power spectra of optical signals $\left(450\sec \right)$ in vitro from the unstimulated lobster nerves. The thick gray line (DARK) shows the spectra of the dark noise with superimposed traces showing the spectra of the LD, LED, and SLD signals transmitted through the lobster nerve. The LD, LED, and SLD signals were normalized to their DC intensities prior to FFT analysis. Note that the spectral power scale for the LD data is two orders of magnitude greater than the DARK, LED, or SLD power across all frequencies.

3.3.

Physiological Noise

The FFTs of the in vitro signals recorded in the presence of a healthy nerve yielded no significant peaks different from trials recorded with a dead nerve (data not shown). Figure 3 shows FFTs of in vitro data for the live nerve under LED, SLD, and LD illumination. Before taking the FFT, each data set was divided by the baseline intensity to control for intensity variations. The FFT data illustrates $1∕f$ noise present, and LD noise power was two orders of magnitude greater than the SLD and LED spectra across all frequencies.

Rat optical noise spectra featured peaks at $3.36\pm 0.42\mathrm{Hz}$ and $1.37\pm 0.47\mathrm{Hz}$ during anesthesia. These peaks were absent from data collected after the rat was euthanized (Fig. 4 ). The low-frequency power was also reduced in dead tissue. The $1∕f$ , cardiac, and respiratory peaks in the LED FFT [Fig. 4b] were equivalent in amplitude to the LD FFT [Fig. 4a].

Fig. 4

Power spectra of optical signals in vivo with an (a) LD, and (b) LED source. Both spectra feature peaks that correspond to $1∕f$ , respiratory $\left(0.9\mathrm{Hz}\right)$ , and cardiac signatures $\left(3.5\mathrm{Hz}\right)$ . Since low-frequency components below $0.5\mathrm{Hz}$ are greater in the live rat, we assume that slow vascular oscillations (Mayer waves) may contribute to noise in this frequency range.

Table 1 shows the RMS noise contributions in the cardiac $(\sim 3\mathrm{Hz})$ , respiratory $(\sim 1\mathrm{Hz})$ , and slow vascular $\left(0\text{to}0.4\mathrm{Hz}\right)$ frequencies. The euthanized rat optical RMS was subtracted from the live rat optical RMS in quadrature to find physiological noise RMS in each characteristic frequency band.

3.4.

In Vitro Paradigm

The illumination intensity for the laser was limited by the dynamic range of the photodiode amplifiers. LED and SLD sources were driven at maximum intensity without approaching the rails of the photodiode amplifier. Baseline measured radiant power for the transmission birefringence data was $0.57\text{to}0.74\mu \mathrm{W}$ for the LD, $0.36\text{to}0.51\mu \mathrm{W}$ for the SLD, and $3.1\text{to}3.3\mu \mathrm{W}$ for the LED.

We defined signal amplitude as the difference between the monophasic optical peak and the baseline. Signal amplitudes ranged from $-1.4$ to $-8.0\times {10}^{-5}dI∕I$ (Fig. 5 ) or $4.4\text{to}54\mu \mathrm{V}$ after 1000 averages. The optical changes were rapid ( $5\text{to}15\mathrm{ms}$ from stimulus to peak) and short in duration $(<30\mathrm{ms})$ . The highest amplitude optical changes occurred at the beginning of each experiment ( $-0.6$ to $-2.9\times {10}^{-4}dI∕I$ or $14\text{to}186\mu \mathrm{V}$ after 100 averages) and then degraded over the $17\text{-}\text{to}33\text{-}\text{minute}$ recording periods (1000 stimuli at $1\text{to}2\sec$ random interstimulus intervals). As shown in Table 1, SNRs for single-pass measurements in lobster nerves with LED illumination were approximately 1:1. Additional filtering $\left(1\text{to}100\mathrm{Hz}\right)$ improved SNRs to about 10:1. More than 150 averaged trials were required to discern the birefringence signal in LD data, even after bandpass filtering. For LD lobster data, the illumination intensity was about 2 times dimmer due to the high peak-to-peak noise from the LD. Since the eventual size of the signal appeared to depend on the illumination intensity, raw signals measured with the LD were lower. However, after dividing the absolute signal size by illumination intensity, the $dI∕I$ values were comparable between LED and LD sources (Fig. 5).

Fig. 5

In vitro optical data for LED, SLD, and LD from stimulated lobster nerves. Black traces show the optical signals $(dI∕I)$ , and gray traces show the stimulus-evoked field potential. The vertical line indicates the time of stimulus. Each trace represents the average of 1000 trials.

Figure 6a shows the mean and standard error of RMS noise calculated for each source across 1000 averages. RMS fell steeply in the first 100 averages, and then continued to decrease gradually from 200 to 1000 averages. RMS levels were greatest for LD, SLD, and LED data, respectively [Fig. 6a]; these differences were further exaggerated when the RMS levels were normalized to the intensity of each source [Fig. 6b]. Figure 7 compares the mean SNR for optical signals collected with the three sources across 1000 averages. The LED average SNRs increased proportional to the square root of the number of averages, peaked near 150 averages, and then gradually decreased with the degradation of the nerve over time. The SLD data had significantly lower SNRs than the LED data, and SNRs for LD data were significantly smaller than LED or SLD SNRs across 1000 averages. The LD SNRs were highly variable in the first 200 trials because the signal was significantly below the noise for the LD light source.

Fig. 6

RMS noise and RMS/RF across averages in vitro from the stimulated lobster nerves. (a) Mean and standard error for RMS noise in transmission birefringence signals for the LED, SLD, and LD across 1000 averages. LED RMS values were 0.62 for single-pass and 0.029 at 1000 averages. The same is shown in (b) except the RMS has been normalized to the RF of each source. LED RMS/RF values are $4.2\times {10}^{-4}$ for single-pass and $1.9\times {10}^{-5}$ at 1000 averages. Each line represents $n=3$ nerves. The measured baseline radiant power in vitro was $0.57\text{to}0.74\mu \mathrm{W}$ for the LD, $0.36\text{to}0.51\mu \mathrm{W}$ for the SLD, and $3.1\text{to}3.3\mu \mathrm{W}$ for the LED.

Fig. 7

Mean and standard error of SNRs ( $dI∕I$ divided by RMS) of the in vitro transmission birefringence changes from the stimulated lobster nerves for three light sources across 1000 averages. Each line represents the average of $n=3$ nerves. The black line is the mean, and the gray background illustrates standard error. The gradual decrease of the LED SNRs after the peak at 150 averages reflects nerve degradation over time.

3.5.

In Vivo Paradigm

Unlike the in vitro optical data, the in vivo optical $dI∕I$ amplitude varied greatly from rat to rat depending on illumination and photodiode placement relative to the activated area (Fig. 8 ). Therefore, we chose to display separately the mean SNR data from three rats rather than the mean and standard error across the three rats to illustrate the variability in signals we observed between rats. Figure 8 displays the FFT analysis of rat optical data (no stimuli) before and after applying the cardiac filter. As has been demonstrated by others,^{12, 22} the cardiac filter reduces the cardiac peak at $2.9\mathrm{Hz}$ by a factor of 90. Similar to the in vitro paradigm, the LD illumination intensity was limited by the dynamic range of the amplifier, while the LED was driven to maximum intensity. The measured baseline radiant power for the rat scattered-light data was $0.84\text{to}1.27\mu \mathrm{W}$ for the LD and $0.81\text{to}2.07\mu \mathrm{W}$ for the LED.

Fig. 8

In vivo optical data during rat whisker twitches. Black traces show cardiac substracted homodynamic optical changes during and after whisker twitch stimulation (5-twitch burst at $10\mathrm{Hz}$ , $7.5\text{-}\sec$ interstimulus intervals, 200 averages). Vertical lines indicate the beginning of the burst. Data are displayed for three rats (R1, R2, and R3) with LED (left column) and LD (right column) illumination. The gray traces for rat R3 show the precardiac filtered signal (Raw), and without stimulation (No Stim). An inset FFT of the R3 data pre-(gray trace) and post-(black trace) cardiac filtering shows removal of the $2.8\text{-}\mathrm{Hz}$ peak.

The optical signals featured a triphasic, hemodynamic response described in detail by several studies.^{23, 24} With the signal amplitude defined as the difference between the first peak at $\sim 3\sec$ and subsequent trough at $\sim 5\sec$ , the $dI∕I$ amplitude ranged from 0.9 to $7.7\times {10}^{-4}$ , or $60\text{to}900\mu \mathrm{V}$ . The lower left waveform in Fig. 8 displays the optical data before and after cardiac subtraction. Figure 9a shows the average and standard error of RMS noise calculated across 200 averages. We divided each RMS value by the baseline light intensity to control for varied illumination intensities [Fig. 9b]. The RMS and RMS/RF for the LD were three times greater than the LED RMS or RMS/RF in single-pass trials, and LD noise continued to be significantly higher than LED noise across 200 averages. Figure 10 separately plots mean SNRs across the number of averages per bin for three rats (R1, R2, R3). In all cases, the mean SNRs obtained under LED illumination increased in fewer averages than the LD SNRs (Fig. 10).

Fig. 9

RMS noise across averages in vivo during rat whisker twitches. (a) Mean (black line) and standard error (gray background) for RMS noise in cardiac-subtracted homodynamic signals for the LED and LD from 1 to 200 averages. The same is shown in (b) except the RMS has been normalized to the RF of each source. Measured baseline radiant power in vivo was $0.84\text{to}1.27\mu \mathrm{W}$ for the LD and $0.81\text{to}2.07\mu \mathrm{W}$ for the LED.

Fig. 10

SNRs for in vivo optical data using LED and LD light sources during rat whisker twitches across the number of averages per bin for rats R1, R2, and R3.

4.1.

Source-Detector Noise

At low intensities, the RMS/RF curves for all sources looked identical, rapidly decreasing with increasing RF, which was expected because the relative contributions of shot noise and photodiode dark current decreased relative to other noise sources at higher intensities. When plotting RMS noise against radiant power, the laser’s sharp increase in RMS at $0.5\mathrm{mW}$ reflects the noise introduced as the LD transitioned from LED mode to lasing. After the transition to lasing, the LD’s RMS remained significantly higher than the LED or SLD RMS, implicating speckle as a possible disadvantage of coherent light sources. Although speckle interference patterns were not directly characterized in these experiments, the sharp increase in RMS noise concomitant with the laser’s transition from LED mode to lasing suggests that speckle arising from self-interference of coherent light may have contributed significantly to the LD instrument noise. Additionally, our previous studies using CCD imaging technology used LEDs specifically because we observed a significant speckle pattern in the images obtained with LDs.²³

Similar to the noncoherent LED, the noise profile of the semicoherent SLD increased linearly with increasing RF, indicating the absence of a transition point in this source. Above intensities dominated by shot noise, SLD RMS increased at a faster rate than LED RMS [Fig. 2a], suggesting that speckle noise also may have contributed significantly to the SLD noise profile or that this light source is less stable. The intensity-normalized FFTs of LD, SLD, and LD signals in vitro (Fig. 3) showed that the LD had a frequency power two orders of magnitude greater than the LED or SLD across all frequencies, again reflecting contributions from white noise sources such as speckle.

4.2.

Physiological Noise

For the in vitro recordings, the similarity between the live-nerve and dead-nerve FFTs suggests that any cellular-or molecular-level noise contributions fell below the sensitivity of the recording method. In vivo, two peaks present in the live-rat FFT and absent in the euthanized-rat FFT corresponded to physiological noise generators: cardiac at $3.5\mathrm{Hz}$ , and respiration at $1.0\mathrm{Hz}$ . Both the LED and LD FFTs also had power in the low frequencies corresponding to $1∕f$ noise; however, the low-frequency density was greater in the live rats than in the euthanized rats, suggesting that other low-frequency physiological sources may have contributed to the low frequencies. For example, in vivo signals may also contain Mayer waves ( $f=0.1\text{to}0.4\mathrm{Hz}$ , Ref. 25), spontaneous oscillations of arterial pressure tightly coupled with the oscillations of efferent sympathetic nervous system activity (for review, see Ref. 26). However, in optical recordings, $1∕f$ noise dominates at these low frequencies, and we attempted to separate the effects of Mayer waves from the $1∕f$ contribution by subtracting live and dead animal recordings for frequencies between 0 and $0.4\mathrm{Hz}$ (Table 1).

As LD intensity increased, so did the noise. Since the input range of the photodiode system was limited, we could only increase the laser diode intensity until the variability (perhaps due to the speckle noise) began to saturate the dynamic range of the photodiode system. Ideally, the brighter the light source, the bigger the SNR of the optical signal by overcoming shot noise limitations; however, the added noise of the LD counteracted gains over the shot noise achieved with brighter illumination.

4.3.

In Vitro Paradigm

Since physiological noise sources were low in vitro, higher SNRs were observed due to lower overall RMS noise. The LED SNR profile peaked at 150 averages, but then decreased over the next 850 averages because nerve health and corresponding signal amplitude decayed over time. Laser diode noise failed to increase with the square root of the number of trials like the LED and SLD SNRs, because below 200 averages, the signal size was significantly below LD noise levels, causing the SNRs in the 1 to 200 trial range to appear variable. The reduced light source noise of LEDs enabled signal recordings with higher SNRs in fewer averages, an advantage for limited-life, in vitro preparations.

4.4.

In Vivo Paradigm

The high variability in the optical response amplitude across different rats likely resulted from variables such as the position of the photodiode over the whisker barrels and anesthesia depth. Like the in vitro experiments, the higher SNRs of hemodynamic signals with the LED over the LD indicate that LEDs are a better light source for noncoherent neural recording applications. In spite of the long integration times typically used to reduce speckle noise for the slow hemodynamic signals seen here, LEDs maintain a significant advantage, perhaps due to noise reduction at low frequencies.