Neuromarketing has become an academic and commercial area of interest, as the advancements in neural recording techniques and interpreting algorithms have made it an effective tool for recognizing the unspoken response of consumers to the marketing stimuli. This article presents the very first systematic review of the technological advancements in Neuromarketing field over the last 5 years. For this purpose, authors have selected and reviewed a total of 57 relevant literatures from valid databases which directly contribute to the Neuromarketing field with basic or empirical research findings. This review finds consumer goods as the prevalent marketing stimuli used in both product and promotion forms in these selected literatures. A trend of analyzing frontal and prefrontal alpha band signals is observed among the consumer emotion recognition-based experiments, which corresponds to frontal alpha asymmetry theory. The use of electroencephalogram (EEG) is found favorable by many researchers over functional magnetic resonance imaging (fMRI) in video advertisement-based Neuromarketing experiments, apparently due to its low cost and high time resolution advantages. Physiological response measuring techniques such as eye tracking, skin conductance recording, heart rate monitoring, and facial mapping have also been found in these empirical studies exclusively or in parallel with brain recordings. Alongside traditional filtering methods, independent component analysis (ICA) was found most commonly in artifact removal from neural signal. In consumer response prediction and classification, Artificial Neural Network (ANN), Support Vector Machine (SVM) and Linear Discriminant Analysis (LDA) have performed with the highest average accuracy among other machine learning algorithms used in these literatures. The authors hope, this review will assist the future researchers with vital information in the field of Neuromarketing for making novel contributions.

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This paper compares the performance of Uniform Linear Arrays (ULA), Minimum Redundancy Arrays (MRA) and Co-prime Sensor Arrays (CSA) in terms of the Peak Sidelobe Level (PSL) of their beampatterns. A ULA distributes its sensor elements equidistantly on a line, achieving a PSL of -13.5dB [Van Trees, 2002]. Sparse arrays span the equivalent aperture as a fully populated ULA with fewer sensors providing cost and computational advantages but with higher PSLs. To span a given aperture, MRAs [Moffet, 1968] require the fewest sensors to include all the spatial correlation lags in its co-array [Johnson and Dudgeon, 1993]. A CSA interleaves a pair of ULAs undersampled by co-prime factors [Vaidyanathan and Pal, 2011]. A CSA can be conventionally processed as a single non-uniform array or by product processing of its subarrays. This paper shows only the product processed CSA sharply decreases its PSL with increasing aperture, eventually matching ULA PSLs [Adhikari et al, 2014]. The MRA and linearly processed CSA PSLs remain unaffected by aperture extension, nearly equal to each other and much higher than the ULA PSLs. Thus, the product processed CSA has the best PSL performance among the considered extended sparse arrays. [Work supported by ONR grant N00014-13-1-0230.]

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The reduced number of sensors in sparse arrays create high peak sidelobe levels (PSLs). This letter compares the PSLs of minimum redundancy arrays (MRAs), minimum hole arrays (MHAs), and co-prime sensor arrays (CSAs) (conventionally beamformed and product processed) with fully populated uniform linear arrays (ULAs) as a function of aperture using both numerical simulations and experimental data. This letter finds that PSLs of MRAs, MHAs, and conventionally processed CSAs are much higher than the ULA PSL and are largely insensitive to aperture extension. In contrast, CSA product processing decreases the PSL with increasing aperture, eventually matching the ULA PSL.

Safety of biomedical ultrasound largely depends on controlling cavitation bubbles in vivo, yet bubble nuclei in biological tissues remain unexplored compared to water. This study evaluates the effects of elastic modulus (E) and impurities on bubble nuclei available for cavitation in tissue-mimicking polyacrylamide (PA) hydrogels. A 1.5 MHz focused ultrasound transducer with f# = 0.7 was used to induce cavitation in 17.5%, 20%, and 22.5% v/v PA hydrogels using 10-ms pulses with pressures up to peak negative pressure (p−) = 35 MPa. Cavitation was monitored at 0.075 ms through high-speed photography at 40 000 fps. At p− = 29 MPa for all hydrogels, cavitation occurred at random locations within the −6 dB focal area [9.4 × 1.2 mm (p−)]. Increasing p− to 35 MPa increased bubble location consistency and caused shock scattering in the E = 282 MPa hydrogels; as the E increased to 300 MPa, bubble location consistency decreased ( p = 0.045). Adding calcium phosphate or cholesterol at 0.25% w/v or bovine serum albumin at 5% or 10% w/v in separate 17.5% PA as impurities decreased the cavitation threshold from p− = 13.2 MPa for unaltered PA to p− = 11.6 MPa, p− = 7.3 MPa, p− = 9.7 MPa, and p− = 7.5 MPa, respectively. These results suggest that both E and impurities affect the bubble nuclei available for cavitation in tissue-mimicking hydrogels.

Tissue mimicking hydrogels can help us understand how viscoelastic properties (stiffness, elastic modulus, etc.) of biological tissues impact bubble nucleation. Adding impurities to hydrogels introduces inhomogeneities and increases their similarity to biological tissues. In this study, we evaluated the effect of stiffness and impurities on bubble nucleation in polyacrylamide (PA) hydrogels. Bubble nuclei were evaluated in 17.5%, 20%, and 22.5% v/v PA hydrogels, after which 0.25% w/v cholesterol crystals (maximum dimension = 0.6 mm) were embedded in the gels (n = 3 each). A 1.5 MHz focused ultrasound transducer was used to induce cavitation using 10-ms pulses with pressures ranging up to p+ = 89 MPa, and p− = 26 MPa and −6 dB focal dimensions of 9.4 × 1.2 mm (p−). Image analysis from high-speed photography showed bubble nucleation increases with increasing peak negative pressure and decreasing hydrogel stiffness. Adding cholesterol crystals largely decreases the acoustic cavitation threshold from p− = 19 MPa for 17.5% v/v hydrogels with no added impurities to p− = 12 MPa for the same concentration hydrogel with added cholesterol crystals. This suggests that hydrophobic cholesterol crystals weaken the gel or trap bubble nuclei, thus lowering the cavitation threshold. Future work includes investigating bubble nuclei in rat hepatocytes. [Work supported by NSF CAREER 1943937 and PSU Riess Fellowship.]

Bubble nuclei have been studied extensively in water for over 50 years with nuclei categorized as homogeneous or heterogeneous. However, it is unclear how those nuclei identified in water translate to viscoelastic hydrogels or tissues. In this study, bubble nuclei were evaluated in 17.5%, 20%, and 22.5% v/v% polyacrylamide (PA) hydrogels (n = 3 each). A 1.5 MHz focused ultrasound transducer was used to induce cavitation using 10-ms pulses with pressures ranging up to p+ = 8 = 89 MPa, and p− = 2 = 26 MPa and -6 dB focal dimensions of 9.4 × 1.15 mm2 (p−). Cavitation size and location were monitored with high-speed photography. When the concentration of PA increased from 17.5% to 20%, the area occupied by bubbles at 0.07 ms decreased from 0.14 mm2 to 0.06 mm2. The location of acoustic cavitation for replicate exposures in the 17.5% gel at 0.07 ms became more consistent as the acoustic pressure increased with no bubble overlap at p− = 2 = 21MPa and 18% bubble overlap at p− = 2 = 26MPa. These results suggest acoustic cavitation in PA hydrogels is dependent on the availability of bubble nuclei at each driving pressure. Future work includes investigating the distribution of bubble nuclei in tissues. [Work supported by NSF CAREER 1943937 and PSU Riess Fellowship].