Work with thought leaders and academic experts in cognitive neuroscience
Companies can greatly benefit from working with experts in the field of Cognitive Neuroscience. These researchers can provide valuable insights into consumer behavior, decision-making processes, and the impact of various stimuli on the brain. By collaborating with Cognitive Neuroscience experts, companies can enhance their research and development efforts, optimize product design and user experience, and create more effective marketing strategies. Additionally, these experts can help companies understand the neural mechanisms underlying mental health disorders and develop innovative solutions for treatment and prevention. Overall, partnering with Cognitive Neuroscience researchers can lead to improved business outcomes and a competitive edge in the market.
Experts on NotedSource with backgrounds in cognitive neuroscience include Yseult Héjja-Brichard, Ph.D., Daniel Milej, Ph.D., Dr. Charles Lassiter, Ph.D., Jo Boaler, Ryan Howell, Suhas Chelian, Suhang Wang, Sonja Lyubomirsky, Norman Farb, Steve Joordens, Ping Luo, Nora S Vyas, Ph.D., and K. Suzanne Scherf.
Yseult Héjja-Brichard, Ph.D.
Postdoctoral researcher in Biological Sciences at University of Maryland Baltimore County
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11 total publications
Processing of Egomotion-Consistent Optic Flow in the Rhesus Macaque Cortex
Cerebral Cortex / Jan 19, 2017
Cottereau, B. R., Smith, A. T., Rima, S., Fize, D., Héjja-Brichard, Y., Renaud, L., Lejards, C., Vayssière, N., Trotter, Y., & Durand, J.-B. (2017). Processing of Egomotion-Consistent Optic Flow in the Rhesus Macaque Cortex. Cerebral Cortex. https://doi.org/10.1093/cercor/bhw412
Connectivity of the Cingulate Sulcus Visual Area (CSv) in Macaque Monkeys
Cerebral Cortex / Oct 17, 2020
De Castro, V., Smith, A. T., Beer, A. L., Leguen, C., Vayssière, N., Héjja-Brichard, Y., Audurier, P., Cottereau, B. R., & Durand, J. B. (2020). Connectivity of the Cingulate Sulcus Visual Area (CSv) in Macaque Monkeys. Cerebral Cortex, 31(2), 1347–1364. https://doi.org/10.1093/cercor/bhaa301
Stereomotion Processing in the Nonhuman Primate Brain
Cerebral Cortex / Mar 28, 2020
Héjja-Brichard, Y., Rima, S., Rapha, E., Durand, J.-B., & Cottereau, B. R. (2020). Stereomotion Processing in the Nonhuman Primate Brain. Cerebral Cortex, 30(8), 4528–4543. https://doi.org/10.1093/cercor/bhaa055
Good scientific practice in EEG and MEG research: Progress and perspectives
NeuroImage / Aug 01, 2022
Niso, G., Krol, L. R., Combrisson, E., Dubarry, A. S., Elliott, M. A., François, C., Héjja-Brichard, Y., Herbst, S. K., Jerbi, K., Kovic, V., Lehongre, K., Luck, S. J., Mercier, M., Mosher, J. C., Pavlov, Y. G., Puce, A., Schettino, A., Schön, D., Sinnott-Armstrong, W., … Chaumon, M. (2022). Good scientific practice in EEG and MEG research: Progress and perspectives. NeuroImage, 257, 119056. https://doi.org/10.1016/j.neuroimage.2022.119056
Symmetry Processing in the Macaque Visual Cortex
Cerebral Cortex / Oct 06, 2021
Audurier, P., Héjja-Brichard, Y., De Castro, V., Kohler, P. J., Norcia, A. M., Durand, J.-B., & Cottereau, B. R. (2021). Symmetry Processing in the Macaque Visual Cortex. Cerebral Cortex, 32(10), 2277–2290. https://doi.org/10.1093/cercor/bhab358
Daniel Milej, Ph.D.
Ph.D. in biomedical engineering
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91 total publications
Assessment of cerebral perfusion in post-traumatic brain injury patients with the use of ICG-bolus tracking method
NeuroImage / Jan 01, 2014
Weigl, W., Milej, D., Gerega, A., Toczylowska, B., Kacprzak, M., Sawosz, P., Botwicz, M., Maniewski, R., Mayzner-Zawadzka, E., & Liebert, A. (2014). Assessment of cerebral perfusion in post-traumatic brain injury patients with the use of ICG-bolus tracking method. NeuroImage, 85, 555–565. https://doi.org/10.1016/j.neuroimage.2013.06.065
Dr. Charles Lassiter, Ph.D.
Associate professor of philosophy with publications on mind, language, knowledge, and culture
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22 total publications
Review of David Chalmers, Reality+: virtual Worlds and the problems of Philosophy, New York: W.W. Norton & Company, 2022
Phenomenology and the Cognitive Sciences / Oct 20, 2022
Lassiter, C., & Kagan, A. (2022). Review of David Chalmers, Reality+: virtual Worlds and the problems of Philosophy, New York: W.W. Norton & Company, 2022. Phenomenology and the Cognitive Sciences. https://doi.org/10.1007/s11097-022-09864-0
New Ontological Foundations for Extended Minds: Causal Powers Realism
Phenomenology and the Cognitive Sciences / Jun 10, 2022
Lassiter, C., & Vukov, J. (2022). New Ontological Foundations for Extended Minds: Causal Powers Realism. Phenomenology and the Cognitive Sciences. https://doi.org/10.1007/s11097-022-09817-7
Jo Boaler
Professor of Mathematics Education, Stanford University
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81 total publications
Obituary
Journal of Fluency Disorders / Jun 01, 2015
Obituary. (2015). Journal of Fluency Disorders, 44, 96. https://doi.org/10.1016/s0094-730x(15)00047-9
Ryan Howell
Professor of Psychology, Department of Psychology, San Francisco State University
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66 total publications
Video conferencing during emergency distance learning impacted student emotions during COVID-19
Computers in Human Behavior Reports / Aug 01, 2022
Okabe-Miyamoto, K., Durnell, E., Howell, R. T., & Zizi, M. (2022). Video conferencing during emergency distance learning impacted student emotions during COVID-19. Computers in Human Behavior Reports, 7, 100199. https://doi.org/10.1016/j.chbr.2022.100199
Suhas Chelian
Lead in machine learning, neuroscience
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18 total publications
Executive control of cognitive agents using a biologically inspired model architecture of the prefrontal cortex
Biologically Inspired Cognitive Architectures / Oct 01, 2012
Srinivasa, N., & Chelian, S. E. (2012). Executive control of cognitive agents using a biologically inspired model architecture of the prefrontal cortex. Biologically Inspired Cognitive Architectures, 2, 13–24. https://doi.org/10.1016/j.bica.2012.07.001
Application of a neural network model of prefrontal cortex to emulate human probability matching behavior
Biologically Inspired Cognitive Architectures / Oct 01, 2014
Chelian, S. E., Uhlenbrock, R. M., Herd, S., & Bhattacharyya, R. (2014). Application of a neural network model of prefrontal cortex to emulate human probability matching behavior. Biologically Inspired Cognitive Architectures, 10, 10–16. https://doi.org/10.1016/j.bica.2014.11.002
Forensic foraging of change detection in opponent strategies with a neural model of the interactions between temporal and prefrontal cortex
Biologically Inspired Cognitive Architectures / Oct 01, 2014
Phillips, M. E., Chelian, S. E., Pirolli, P., & Bhattacharyya, R. (2014). Forensic foraging of change detection in opponent strategies with a neural model of the interactions between temporal and prefrontal cortex. Biologically Inspired Cognitive Architectures, 10, 17–23. https://doi.org/10.1016/j.bica.2014.11.003
DISCOV (DImensionless Shunting COlor Vision): A neural model for spatial data analysis
Neural Networks / Jan 01, 2013
Carpenter, G. A., & Chelian, S. E. (2013). DISCOV (DImensionless Shunting COlor Vision): A neural model for spatial data analysis. Neural Networks, 37, 93–102. https://doi.org/10.1016/j.neunet.2012.08.012
A model of proactive and reactive cognitive control with anterior cingulate cortex and the neuromodulatory system
Biologically Inspired Cognitive Architectures / Oct 01, 2014
Ziegler, M. D., Chelian, S. E., Benvenuto, J., Krichmar, J. L., O’Reilly, R., & Bhattacharyya, R. (2014). A model of proactive and reactive cognitive control with anterior cingulate cortex and the neuromodulatory system. Biologically Inspired Cognitive Architectures, 10, 61–67. https://doi.org/10.1016/j.bica.2014.11.008
Suhang Wang
Professor at Pennsylvania State University
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92 total publications
Learning Word Representations for Sentiment Analysis
Cognitive Computation / Aug 17, 2017
Li, Y., Pan, Q., Yang, T., Wang, S., Tang, J., & Cambria, E. (2017). Learning Word Representations for Sentiment Analysis. Cognitive Computation, 9(6), 843–851. https://doi.org/10.1007/s12559-017-9492-2
Discriminative graph regularized extreme learning machine and its application to face recognition
Neurocomputing / Feb 01, 2015
Peng, Y., Wang, S., Long, X., & Lu, B.-L. (2015). Discriminative graph regularized extreme learning machine and its application to face recognition. Neurocomputing, 149, 340–353. https://doi.org/10.1016/j.neucom.2013.12.065
Enhanced low-rank representation via sparse manifold adaption for semi-supervised learning
Neural Networks / May 01, 2015
Peng, Y., Lu, B.-L., & Wang, S. (2015). Enhanced low-rank representation via sparse manifold adaption for semi-supervised learning. Neural Networks, 65, 1–17. https://doi.org/10.1016/j.neunet.2015.01.001
Popularity prediction on vacation rental websites
Neurocomputing / Oct 01, 2020
Li, Y., Wang, S., Ma, Y., Pan, Q., & Cambria, E. (2020). Popularity prediction on vacation rental websites. Neurocomputing, 412, 372–380. https://doi.org/10.1016/j.neucom.2020.05.092
Sonja Lyubomirsky
Distinguished Professor, University of California, Riverside
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114 total publications
Experimental effects of social behavior on well-being
Trends in Cognitive Sciences / Nov 01, 2022
Regan, A., Radošić, N., & Lyubomirsky, S. (2022). Experimental effects of social behavior on well-being. Trends in Cognitive Sciences, 26(11), 987–998. https://doi.org/10.1016/j.tics.2022.08.006
Norman Farb
Associate Professor at University of Toronto - Mississauga
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96 total publications
Attending to the present: mindfulness meditation reveals distinct neural modes of self-reference
Social Cognitive and Affective Neuroscience / Aug 13, 2007
Farb, N. A. S., Segal, Z. V., Mayberg, H., Bean, J., McKeon, D., Fatima, Z., & Anderson, A. K. (2007). Attending to the present: mindfulness meditation reveals distinct neural modes of self-reference. Social Cognitive and Affective Neuroscience, 2(4), 313–322. https://doi.org/10.1093/scan/nsm030
Mindfulness meditation training alters cortical representations of interoceptive attention
Social Cognitive and Affective Neuroscience / Jul 06, 2012
Farb, N. A. S., Segal, Z. V., & Anderson, A. K. (2012). Mindfulness meditation training alters cortical representations of interoceptive attention. Social Cognitive and Affective Neuroscience, 8(1), 15–26. https://doi.org/10.1093/scan/nss066
Attentional Modulation of Primary Interoceptive and Exteroceptive Cortices
Cerebral Cortex / Jan 19, 2012
Farb, N. A. S., Segal, Z. V., & Anderson, A. K. (2012). Attentional Modulation of Primary Interoceptive and Exteroceptive Cortices. Cerebral Cortex, 23(1), 114–126. https://doi.org/10.1093/cercor/bhr385
Abnormal network connectivity in frontotemporal dementia: Evidence for prefrontal isolation
Cortex / Jul 01, 2013
Farb, N. A. S., Grady, C. L., Strother, S., Tang-Wai, D. F., Masellis, M., Black, S., Freedman, M., Pollock, B. G., Campbell, K. L., Hasher, L., & Chow, T. W. (2013). Abnormal network connectivity in frontotemporal dementia: Evidence for prefrontal isolation. Cortex, 49(7), 1856–1873. https://doi.org/10.1016/j.cortex.2012.09.008
Intrinsic medial temporal lobe connectivity relates to individual differences in episodic autobiographical remembering
Cortex / Jan 01, 2016
Sheldon, S., Farb, N., Palombo, D. J., & Levine, B. (2016). Intrinsic medial temporal lobe connectivity relates to individual differences in episodic autobiographical remembering. Cortex, 74, 206–216. https://doi.org/10.1016/j.cortex.2015.11.005
Do Lifestyle Activities Protect Against Cognitive Decline in Aging? A Review
Frontiers in Aging Neuroscience / Nov 20, 2017
Christie, G. J., Hamilton, T., Manor, B. D., Farb, N. A. S., Farzan, F., Sixsmith, A., Temprado, J.-J., & Moreno, S. (2017). Do Lifestyle Activities Protect Against Cognitive Decline in Aging? A Review. Frontiers in Aging Neuroscience, 9. https://doi.org/10.3389/fnagi.2017.00381
Frontoparietal and Default Mode Network Contributions to Self-Referential Processing in Social Anxiety Disorder
Cognitive, Affective, & Behavioral Neuroscience / Aug 02, 2021
Dixon, M. L., Moodie, C. A., Goldin, P. R., Farb, N., Heimberg, R. G., Zhang, J., & Gross, J. J. (2021). Frontoparietal and Default Mode Network Contributions to Self-Referential Processing in Social Anxiety Disorder. Cognitive, Affective, & Behavioral Neuroscience, 22(1), 187–198. https://doi.org/10.3758/s13415-021-00933-6
Facial emotion recognition in children treated for posterior fossa tumours and typically developing children: A divergence of predictors
NeuroImage: Clinical / Jan 01, 2019
Moxon-Emre, I., Farb, N. A. S., Oyefiade, A. A., Bouffet, E., Laughlin, S., Skocic, J., de Medeiros, C. B., & Mabbott, D. J. (2019). Facial emotion recognition in children treated for posterior fossa tumours and typically developing children: A divergence of predictors. NeuroImage: Clinical, 23, 101886. https://doi.org/10.1016/j.nicl.2019.101886
Static and treatment-responsive brain biomarkers of depression relapse vulnerability following prophylactic psychotherapy: Evidence from a randomized control trial
NeuroImage: Clinical / Jan 01, 2022
Farb, N. A. S., Desormeau, P., Anderson, A. K., & Segal, Z. V. (2022). Static and treatment-responsive brain biomarkers of depression relapse vulnerability following prophylactic psychotherapy: Evidence from a randomized control trial. NeuroImage: Clinical, 34, 102969. https://doi.org/10.1016/j.nicl.2022.102969
Emotion Regulation in Social Anxiety Disorder: Reappraisal and Acceptance of Negative Self-beliefs
Biological Psychiatry: Cognitive Neuroscience and Neuroimaging / Jan 01, 2020
Dixon, M. L., Moodie, C. A., Goldin, P. R., Farb, N., Heimberg, R. G., & Gross, J. J. (2020). Emotion Regulation in Social Anxiety Disorder: Reappraisal and Acceptance of Negative Self-beliefs. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 5(1), 119–129. https://doi.org/10.1016/j.bpsc.2019.07.009
Steve Joordens
UofT Professor of Psychology with a passion for preventive mental health and education
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77 total publications
EEG variability: Task-driven or subject-driven signal of interest?
NeuroImage / May 01, 2022
Gibson, E., Lobaugh, N. J., Joordens, S., & McIntosh, A. R. (2022). EEG variability: Task-driven or subject-driven signal of interest? NeuroImage, 252, 119034. https://doi.org/10.1016/j.neuroimage.2022.119034
Ping Luo
Postdoctoral Researcher at Princess Margaret Cancer Centre with experience in deep learning
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23 total publications
CASNMF: A Converged Algorithm for symmetrical nonnegative matrix factorization
Neurocomputing / Jan 01, 2018
Tian, L.-P., Luo, P., Wang, H., Zheng, H., & Wu, F.-X. (2018). CASNMF: A Converged Algorithm for symmetrical nonnegative matrix factorization. Neurocomputing, 275, 2031–2040. https://doi.org/10.1016/j.neucom.2017.10.039
Nora S Vyas, Ph.D.
Associate Professor of Mental Health, with interest in civic engagement and partnerships
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30 total publications
Reading abilities and dopamine D2/D3 receptor availability: An inverted U-shaped association in subjects with schizophrenia
Brain and Language / Dec 01, 2021
Mitelman, S. A., Buchsbaum, M. S., Vyas, N. S., Christian, B. T., Merrill, B. M., Buchsbaum, B. R., Mitelman, A. M., Mukherjee, J., & Lehrer, D. S. (2021). Reading abilities and dopamine D2/D3 receptor availability: An inverted U-shaped association in subjects with schizophrenia. Brain and Language, 223, 105046. https://doi.org/10.1016/j.bandl.2021.105046
K. Suzanne Scherf
Associate Professor of Psychology & Neuroscience, Penn State University
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80 total publications
Visual category-selectivity for faces, places and objects emerges along different developmental trajectories
Developmental Science / Jul 01, 2007
Scherf, K. S., Behrmann, M., Humphreys, K., & Luna, B. (2007). Visual category-selectivity for faces, places and objects emerges along different developmental trajectories. Developmental Science, 10(4), F15–F30. https://doi.org/10.1111/j.1467-7687.2007.00595.x
Brain Basis of Developmental Change in Visuospatial Working Memory
Journal of Cognitive Neuroscience / Jul 01, 2006
Scherf, K. S., Sweeney, J. A., & Luna, B. (2006). Brain Basis of Developmental Change in Visuospatial Working Memory. Journal of Cognitive Neuroscience, 18(7), 1045–1058. https://doi.org/10.1162/jocn.2006.18.7.1045
Facing changes and changing faces in adolescence: A new model for investigating adolescent-specific interactions between pubertal, brain and behavioral development
Developmental Cognitive Neuroscience / Apr 01, 2012
Scherf, K. S., Behrmann, M., & Dahl, R. E. (2012). Facing changes and changing faces in adolescence: A new model for investigating adolescent-specific interactions between pubertal, brain and behavioral development. Developmental Cognitive Neuroscience, 2(2), 199–219. https://doi.org/10.1016/j.dcn.2011.07.016
Two faces, two languages: An fMRI study of bilingual picture naming
Brain and Language / Dec 01, 2013
Li, Y., Yang, J., Suzanne Scherf, K., & Li, P. (2013). Two faces, two languages: An fMRI study of bilingual picture naming. Brain and Language, 127(3), 452–462. https://doi.org/10.1016/j.bandl.2013.09.005
Pubertal development shapes perception of complex facial expressions
Developmental Science / Jun 19, 2016
Motta‐Mena, N. V., & Scherf, K. S. (2016). Pubertal development shapes perception of complex facial expressions. Developmental Science, 20(4). Portico. https://doi.org/10.1111/desc.12451
Beyond the FFA: Brain-behavior correspondences in face recognition abilities
NeuroImage / Feb 01, 2017
Elbich, D. B., & Scherf, S. (2017). Beyond the FFA: Brain-behavior correspondences in face recognition abilities. NeuroImage, 147, 409–422. https://doi.org/10.1016/j.neuroimage.2016.12.042
Young children's neural processing of their mother’s voice: An fMRI study
Neuropsychologia / Jan 01, 2019
Liu, P., Cole, P. M., Gilmore, R. O., Pérez-Edgar, K. E., Vigeant, M. C., Moriarty, P., & Scherf, K. S. (2019). Young children’s neural processing of their mother’s voice: An fMRI study. Neuropsychologia, 122, 11–19. https://doi.org/10.1016/j.neuropsychologia.2018.12.003
Young children's neural processing of their mother’s voice: An fMRI study
Neuropsychologia / Jan 01, 2019
Liu, P., Cole, P. M., Gilmore, R. O., Pérez-Edgar, K. E., Vigeant, M. C., Moriarty, P., & Scherf, K. S. (2019). Young children’s neural processing of their mother’s voice: An fMRI study. Neuropsychologia, 122, 11–19. https://doi.org/10.1016/j.neuropsychologia.2018.12.003
Configural processing in autism and its relationship to face processing
Neuropsychologia / Jan 01, 2006
Behrmann, M., Avidan, G., Leonard, G. L., Kimchi, R., Luna, B., Humphreys, K., & Minshew, N. (2006). Configural processing in autism and its relationship to face processing. Neuropsychologia, 44(1), 110–129. https://doi.org/10.1016/j.neuropsychologia.2005.04.002
The Privileged Status of Peer Faces: Subordinate-level Neural Representations of Faces in Emerging Adults
Journal of Cognitive Neuroscience / Jan 01, 2023
Dai, J., & Scherf, K. S. (2023). The Privileged Status of Peer Faces: Subordinate-level Neural Representations of Faces in Emerging Adults. Journal of Cognitive Neuroscience, 35(4), 715–735. https://doi.org/10.1162/jocn_a_01966
Changes in Cortical Coherence Supporting Complex Visual and Social Processing in Adolescence
Journal of Cognitive Neuroscience / Oct 01, 2021
Lerner, Y., Scherf, K. S., Katkov, M., Hasson, U., & Behrmann, M. (2021). Changes in Cortical Coherence Supporting Complex Visual and Social Processing in Adolescence. Journal of Cognitive Neuroscience, 33(11), 2215–2230. https://doi.org/10.1162/jocn_a_01756
Puberty and functional brain development in humans: Convergence in findings?
Developmental Cognitive Neuroscience / Oct 01, 2019
Dai, J., & Scherf, K. S. (2019). Puberty and functional brain development in humans: Convergence in findings? Developmental Cognitive Neuroscience, 39, 100690. https://doi.org/10.1016/j.dcn.2019.100690
A theoretical rut: revisiting and critically evaluating the generalized under/over‐connectivity hypothesis of autism
Developmental Science / Jul 01, 2016
Picci, G., Gotts, S. J., & Scherf, K. S. (2016). A theoretical rut: revisiting and critically evaluating the generalized under/over‐connectivity hypothesis of autism. Developmental Science, 19(4), 524–549. Portico. https://doi.org/10.1111/desc.12467
Animal, but not human, faces engage the distributed face network in adolescents with autism
Developmental Science / Apr 14, 2015
Whyte, E. M., Behrmann, M., Minshew, N. J., Garcia, N. V., & Scherf, K. S. (2015). Animal, but not human, faces engage the distributed face network in adolescents with autism. Developmental Science, 19(2), 306–317. Portico. https://doi.org/10.1111/desc.12305
Size Precedes View: Developmental Emergence of Invariant Object Representations in Lateral Occipital Complex
Journal of Cognitive Neuroscience / Mar 01, 2015
Nishimura, M., Scherf, K. S., Zachariou, V., Tarr, M. J., & Behrmann, M. (2015). Size Precedes View: Developmental Emergence of Invariant Object Representations in Lateral Occipital Complex. Journal of Cognitive Neuroscience, 27(3), 474–491. https://doi.org/10.1162/jocn_a_00720
Individual differences in symptom severity and behavior predict neural activation during face processing in adolescents with autism
NeuroImage: Clinical / Jan 01, 2015
Scherf, K. S., Elbich, D., Minshew, N., & Behrmann, M. (2015). Individual differences in symptom severity and behavior predict neural activation during face processing in adolescents with autism. NeuroImage: Clinical, 7, 53–67. https://doi.org/10.1016/j.nicl.2014.11.003
Emerging Structure-Function Relations in the Developing Face Processing System
Cerebral Cortex / Jun 13, 2013
Scherf, K. S., Thomas, C., Doyle, J., & Behrmann, M. (2013). Emerging Structure-Function Relations in the Developing Face Processing System. Cerebral Cortex, 24(11), 2964–2980. https://doi.org/10.1093/cercor/bht152
"What" Precedes "Which": Developmental Neural Tuning in Face- and Place-Related Cortex
Cerebral Cortex / Jan 21, 2011
Scherf, K. S., Luna, B., Avidan, G., & Behrmann, M. (2011). “What” Precedes “Which”: Developmental Neural Tuning in Face- and Place-Related Cortex. Cerebral Cortex, 21(9), 1963–1980. https://doi.org/10.1093/cercor/bhq269
Example cognitive neuroscience projects
How can companies collaborate more effectively with researchers, experts, and thought leaders to make progress on cognitive neuroscience?
Optimizing User Experience
A tech company can collaborate with a Cognitive Neuroscience expert to optimize the user experience of their digital products. By understanding how the brain processes information and interacts with technology, the researcher can provide valuable insights on improving usability, reducing cognitive load, and enhancing user engagement.
Neuromarketing Research
A marketing agency can partner with a Cognitive Neuroscience researcher to conduct neuromarketing studies. By using techniques such as EEG and fMRI, the researcher can measure consumers' brain responses to marketing stimuli, helping the agency create more persuasive and impactful advertising campaigns.
Understanding Consumer Decision-Making
A consumer goods company can collaborate with a Cognitive Neuroscience expert to gain a deeper understanding of consumer decision-making processes. By studying the neural mechanisms involved in decision-making, the researcher can provide insights on product preferences, pricing strategies, and effective marketing messages.
Developing Brain-Computer Interfaces
A technology company can work with a Cognitive Neuroscience researcher to develop innovative brain-computer interfaces (BCIs). By leveraging their knowledge of neural signals and brain activity, the researcher can contribute to the design and development of BCIs that enable direct communication between the brain and external devices, opening up new possibilities for human-computer interaction.
Improving Mental Health Solutions
A healthcare company can collaborate with a Cognitive Neuroscience expert to improve mental health solutions. By studying the neural basis of mental health disorders, the researcher can contribute to the development of more effective treatments, personalized interventions, and early detection methods.