Brain Imaging
In cognitive science, there is an ongoing debate about the architecture of the mind: does it consist of a number of mental “organs” each managing a different function in isolation, or is it more of general processor, adaptable to a wide... more
In cognitive science, there is an ongoing debate about the architecture of the mind: does it consist of a number of mental “organs” each managing a different function in isolation, or is it more of general processor, adaptable to a wide range of tasks? One corner of this debate has centered on face processing. This is because face-perception is crucial to normal human functioning and some evidence shows that faces may be processed by the brain in a privileged way compared to other types of stimuli. For example, in EEG brain recordings, the N170 is a characteristic spike that occurs after a participant is exposed to an image of a face, but it is much less pronounced when other stimuli are shown. More than 15 years of research on the “N170 face effect” have yielded the standard view that the N170 is at the very least face-sensitive, and possibly even face-specific, that is, indexing modular processes tied exclusively to facial geometries. The specificity claim is stronger, and hence subject to significant controversy; while the more conservative “sensitivity” claim had been regarded (until recently) as effectively settled. Thierry and colleagues, in a contentious 2007 article, sought to undermine this ‘conservative’ consensus by proposing an alternative explanation for the N170, attributing it to poor experimental design. Fiery debate has followed. In this review, we put the debate in its historical and philosophical context, and try to spell out some of the theoretical and logical assumptions that underlie the claims of the competing camps. We then show that the best available evidence counts against the Thierry et al. construal of the N170. That is, their paper is flawed enough to merit a rejection of its main findings and a re-adoption of the “conservative” account of the N170—i.e., that the N170 is at least preferentially responsive to faces. We conclude by returning to the more controversial claim about face-specificity, and try to clarify what such a view would entail from a theoretical standpoint.
Download "As AI and architecture mediate and control their mutual interactions metaphoric axioms will have cognitive impact on both the future of architecture and AI because there is common metaphor between natural (NI) and artificial intelligence... more
"As AI and architecture mediate and control their mutual interactions metaphoric axioms will have cognitive impact on both the future of architecture and AI because there is common metaphor between natural (NI) and artificial intelligence (AI). The inference warrants that for both architectures’ (AI and building) , master builder is an interdisciplinary, multi-crafted and multi-venue team, They are also both arts since they wed intentional ideas to craft and they both make metaphors, the commonality to all the arts. While “architect” actually means master builder and “architecture” the product of the master builder, this is historically identified with habitable buildings. The warrant to the inference of the resolution is that the computer industries (and virtual designers) have made a metaphor referring to the word “architecture” with its conceptual design and fundamental operational structures of computer systems. Already, IT and AI industry metaphorically compare their sciences and art of selecting and interconnecting hardware components to create computers that meet functional, performance and cost goals with the ways and means traditional architects design buildings. There is an interconectivity between the metaphor of computer’s instruction set architecture, or ISA, machine language (or assembly language), Microarchitecture and system design.
Theoretically, I warrant that the as the body and mind of AI has identified itself with “architecture” there is an opportunity to use those links to apply and manage risks of AI to building architecture. However, benign, risks include operating system downtime, programming errors, inaccuracy in labeling and dimensions, misreading building codes, local ordinances, misinterpreting FEMA regulations and potential tampering with building security systems. . Further risks include erroneous selection of material and building systems that may expose architects to errors and omissions suits, so many of the general and specific axioms guidelines can be uploaded into the AI architectural system. So with AI potential risk [ff] what can be the impact of artificial intelligence on the future of building architecture? "
Theoretically, I warrant that the as the body and mind of AI has identified itself with “architecture” there is an opportunity to use those links to apply and manage risks of AI to building architecture. However, benign, risks include operating system downtime, programming errors, inaccuracy in labeling and dimensions, misreading building codes, local ordinances, misinterpreting FEMA regulations and potential tampering with building security systems. . Further risks include erroneous selection of material and building systems that may expose architects to errors and omissions suits, so many of the general and specific axioms guidelines can be uploaded into the AI architectural system. So with AI potential risk [ff] what can be the impact of artificial intelligence on the future of building architecture? "
Download In the Handbook of Neurotoxicology, Volumes I and II, many leading researchers and clinicians-all acknowledged experts-review in depth the status of research in key areas of current neurotoxicologic interest and examine the latest... more
In the Handbook of Neurotoxicology, Volumes I and II, many leading researchers and clinicians-all acknowledged experts-review in depth the status of research in key areas of current neurotoxicologic interest and examine the latest methodologies for in vivo assessment of a wide spectrum of agents exhibiting neurotoxicologic properties. This second volume of the Handbook focuses on the biologic effects of human-made toxins on the developing organism, and of drugs of abuse. Here are discussed the interpretation of neurotoxicity data, the art of risk assessment, and the manifestation of CNS insult during development. The drugs of abuse surveyed include cocaine, marijuana, the cannabinoids, and amphetimines. Also provided are state-of-the-art methods for the evaluation of neurotoxicant effects by both imaging and neurobehavioral assessment. Volume I concentrates on the biological effects of both human-made neurotoxins (pesticides, mercury, lead, zinc, and polytypic byproducts of combustion and manufacture) and those of natural origin (microbial and animal toxins).
The neuroscience of decision making is a rapidly evolving multidisciplinary research area that employs neuroscientific techniques to explain various parameters associated with decision making behavior. In this paper we emphasize the role... more
The neuroscience of decision making is a rapidly evolving multidisciplinary research area that employs neuroscientific techniques to explain various parameters associated with decision making behavior. In this paper we emphasize the role of multiple disciplines such as psychology, economics, neuroscience, and computational approaches in understanding the phenomenon of decision making. Further, we present a theoretical approach that suggests understanding the building-blocks of decision making as bottom-up processes and integrate these with top-down modulatory factors. Relevant neurophysiological and neuroimaging findings that have used the building-block approach are reviewed. A unifying framework emphasizing multidisciplinary views would bring further insights into the active research area of decision making. Pointing to future directions for research, we focus on the role of computational approaches in such a unifying framework.
Human cognition is increasingly characterized as an emergent property of interactions among distributed, functionally specialized brain networks. We recently demonstrated that the antagonistic “default” and “dorsal attention” networks –... more
Human cognition is increasingly characterized as an emergent property of interactions among distributed, functionally specialized brain networks. We recently demonstrated that the antagonistic “default” and “dorsal attention” networks – subserving internally and externally directed cognition, respectively – are modulated by a third “frontoparietal control” network that flexibly couples with either network depending on task domain. However, little is known about the intrinsic functional architecture underlying this relationship. We used graph theory to analyze network properties of intrinsic functional connectivity within and between these three large-scale networks. Task-based activation from three independent studies was used to identify reliable brain regions (“nodes”) of each network. We then examined pairwise connections (“edges”) between nodes, as defined by resting-state functional connectivity MRI. Importantly, we used a novel bootstrap resampling procedure to determine the reliability of graph edges. Further, we examined both full and partial correlations. As predicted, there was a higher degree of integration within each network than between networks. Critically, whereas the default and dorsal attention networks shared little positive connectivity with one another, the frontoparietal control network showed a high degree of between-network interconnectivity with each of these networks. Further, we identified nodes within the frontoparietal control network of three different types – default-aligned, dorsal attention-aligned, and dual-aligned – that we propose play dissociable roles in mediating inter-network communication. The results provide evidence consistent with the idea that the frontoparietal control network plays a pivotal gate-keeping role in goal-directed cognition, mediating the dynamic balance between default and dorsal attention networks.
"Background: Several studies have found widespread structural changes affecting the grey matter at various stages of schizophrenia (the prodrome, first-episode, and the chronic stage). It is unclear which of these neuroanatomical changes... more
"Background: Several studies have found widespread structural changes affecting the grey matter at various stages of schizophrenia (the prodrome, first-episode, and the chronic stage). It is unclear which of these neuroanatomical changes are associated with a predisposition or vulnerability to develop schizophrenia rather than the appearance of the clinical features of the illness.
Methods: 16 voxel-based morphometry (VBM) analyses involving 733 genetically high-risk relatives (HRR) of patients with schizophrenia, 563 healthy controls and 474 patients were meta-analysed using the Signed Differential Mapping (SDM) technique. Two meta-analyses were conducted, with one comparing HRR group with healthy controls and the other comparing HRR group with the patients.
Results: A significant grey matter reduction in the lentiform nucleus, amygdala / parahippocampal gyrus and medial prefrontal cortex was seen in association with the genetic diathesis. Grey matter reduction in bilateral insula, inferior frontal gyrus, superior temporal gyrus and the anterior cingulate was seen in association with the disease expression.
Conclusions: The neuroanatomical changes associated with the genetic diathesis to develop schizophrenia appear to be different from those that contribute to the clinical expression of the illness. Grey matter abnormalities in multimodal brain regions that have a supervisory function are likely to be central to the expression of the clinical symptoms of schizophrenia."
Methods: 16 voxel-based morphometry (VBM) analyses involving 733 genetically high-risk relatives (HRR) of patients with schizophrenia, 563 healthy controls and 474 patients were meta-analysed using the Signed Differential Mapping (SDM) technique. Two meta-analyses were conducted, with one comparing HRR group with healthy controls and the other comparing HRR group with the patients.
Results: A significant grey matter reduction in the lentiform nucleus, amygdala / parahippocampal gyrus and medial prefrontal cortex was seen in association with the genetic diathesis. Grey matter reduction in bilateral insula, inferior frontal gyrus, superior temporal gyrus and the anterior cingulate was seen in association with the disease expression.
Conclusions: The neuroanatomical changes associated with the genetic diathesis to develop schizophrenia appear to be different from those that contribute to the clinical expression of the illness. Grey matter abnormalities in multimodal brain regions that have a supervisory function are likely to be central to the expression of the clinical symptoms of schizophrenia."
To understand the brain areas associated with visual awareness and their anatomical interconnections, we studied binocular rivalry with functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI). Binocular rivalry... more
To understand the brain areas associated with visual awareness and their anatomical interconnections, we studied binocular rivalry with functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI). Binocular rivalry occurs when one image is viewed by one eye and a different image by the other; it is experienced as perceptual alternations between the two images. Our first experiment addressed problems with a popular comparison condition, namely permanent suppression, by comparing rivalry with binocular fusion instead. We found an increased fMRI signal in right frontal, parietal, and occipital regions during rivalry viewing. The pattern of neural activity differed from findings of permanent suppression comparisons, except for adjacent activity in the right superior parietal lobule. This location was near fMRI signal changes related to reported rivalry alternations in our second experiment, indicating that neighbouring areas in the right parietal cortex may be involved in different components of rivalry. In our second experiment, we used probabilistic tractography to detect white matter fibres between right-hemispheric areas that showed event-related fMRI signal changes time-locked to reported perceptual alternations during rivalry viewing. Most of these functionally defined areas were linked by probabilistic fibre tracts, some of which followed long-distance connections such as the inferior occipitofrontal fasciculus. Corresponding anatomical pathways might mediate communication within the functional network associated with changes in conscious perception during binocular rivalry.
The impulsive behavior that is often characteristic of adolescence may reflect underlying neurodevelopmental processes. Moreover, impulsivity is a multi-dimensional construct, and it is plausible that distinct brain networks contribute to... more
The impulsive behavior that is often characteristic of adolescence may reflect underlying neurodevelopmental processes. Moreover, impulsivity is a multi-dimensional construct, and it is plausible that distinct brain networks contribute to its different cognitive, clinical and behavioral aspects. As these networks have not yet been described, we identified distinct cortical and subcortical networks underlying successful inhibitions and inhibition failures in a large sample (n = 1,896) of 14-year-old adolescents. Different networks were associated with drug use (n = 1,593) and attention-deficit hyperactivity disorder symptoms (n = 342). Hypofunctioning of a specific orbitofrontal cortical network was associated with likelihood of initiating drug use in early adolescence. Right inferior frontal activity was related to the speed of the inhibition process (n = 826) and use of illegal substances and associated with genetic variation in a norepinephrine transporter gene (n = 819). Our results indicate that both neural endophenotypes and genetic variation give rise to the various manifestations of impulsive behavior.
Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimer's disease and is... more
Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimer's disease and is reduced in schizophrenia, major depression and mesial temporal lobe epilepsy. Whereas many brain imaging phenotypes are highly heritable, identifying and replicating genetic influences has been difficult, as small effects and the high costs of magnetic resonance imaging (MRI) have led to underpowered studies. Here we report genome-wide association meta-analyses and replication for mean bilateral hippocampal, total brain and intracranial volumes from a large multinational consortium. The intergenic variant rs7294919 was associated with hippocampal volume (12q24.22; N = 21,151; P = 6.70 × 10(-16)) and the expression levels of the positional candidate gene TESC in brain tissue. Additionally, rs10784502, located within HMGA2, was associated with intracranial volume (12q14.3; N = 15,782; P = 1.12 × 10(-12)). We also identified a suggestive association with total brain volume at rs10494373 within DDR2 (1q23.3; N = 6,500; P = 5.81 × 10(-7)).
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We investigate subjects’ brain hemodynamic activities during mental tasks using a nearinfrared spectroscopy. A wavelet and neural network-based methodology is presented for recognition of brain hemodynamic responses. The recognition is... more
We investigate subjects’ brain hemodynamic activities during mental tasks using a nearinfrared spectroscopy. A wavelet and neural network-based methodology is presented for recognition of brain hemodynamic responses. The recognition is performed by a single layer neural network classifier according to a backpropagation algorithm with two error minimizing techniques. The performance of the classifier varied depending on the neural network model, but the performance was usually at least 90%. The classifier usually converged faster and attained a somewhat greater level of performance when an input was presented with only relevant features. The overall classification rate was higher than 94%. The study demonstrates the accurate classifiablity of human brain hemodynamic useful in various brain studies.