[Neurological disease and facial recognition].
Kawamura Mitsuru,Sugimoto Azusa,Kobayakawa Mutsutaka,Tsuruya Natsuko
Brain and nerve = Shinkei kenkyu no shinpo
To discuss the neurological basis of facial recognition, we present our case reports of impaired recognition and a review of previous literature. First, we present a case of infarction and discuss prosopagnosia, which has had a large impact on face recognition research. From a study of patient symptoms, we assume that prosopagnosia may be caused by unilateral right occipitotemporal lesion and right cerebral dominance of facial recognition. Further, circumscribed lesion and degenerative disease may also cause progressive prosopagnosia. Apperceptive prosopagnosia is observed in patients with posterior cortical atrophy (PCA), pathologically considered as Alzheimer's disease, and associative prosopagnosia in frontotemporal lobar degeneration (FTLD). Second, we discuss face recognition as part of communication. Patients with Parkinson disease show social cognitive impairments, such as difficulty in facial expression recognition and deficits in theory of mind as detected by the reading the mind in the eyes test. Pathological and functional imaging studies indicate that social cognitive impairment in Parkinson disease is possibly related to damages in the amygdalae and surrounding limbic system. The social cognitive deficits can be observed in the early stages of Parkinson disease, and even in the prodromal stage, for example, patients with rapid eye movement (REM) sleep behavior disorder (RBD) show impairment in facial expression recognition. Further, patients with myotonic dystrophy type 1 (DM 1), which is a multisystem disease that mainly affects the muscles, show social cognitive impairment similar to that of Parkinson disease. Our previous study showed that facial expression recognition impairment of DM 1 patients is associated with lesion in the amygdalae and insulae. Our study results indicate that behaviors and personality traits in DM 1 patients, which are revealed by social cognitive impairment, are attributable to dysfunction of the limbic system.
A bio-physical basis of mathematics in synaptic function of the nervous system: a theory.
The purpose of this paper is to present a bio-physical basis of mathematics. The essence of the theory is that function in the nervous system is mathematical. The mathematics arises as a result of the interaction of energy (a wave with a precise curvature in space and time) and matter (a molecular or ionic structure with a precise form in space and time). In this interaction, both energy and matter play an active role. That is, the interaction results in a change in form of both energy and matter. There are at least six mathematical operations in a simple synaptic region. It is believed the form of both energy and matter are specific, and their interaction is specific, that is, function in most of the 'mind' and placed where it belongs - in nature and the synaptic regions of the nervous system; it results in both places from a precise interaction between energy (in a precise form) and matter ( in a precise structure).
What do imaging studies tell us about the neural basis of autism?
Novartis Foundation symposium
There is no clear evidence from imaging studies for specific structural abnormalities in the brains of people with autism. The most robust observation is of greater total brain volume. There is evidence that this greater volume is not present at birth, but appears during the first few years. This brain enlargement might be a marker of abnormal connectivity due to lack of pruning. While abnormalities have often been reported in the cerebellum and the amygdala, these are difficult to interpret since both increases and decreases in the size of these structures have been observed. Another way of identifying the neural basis of autism is to investigate brain systems underlying cognitive functions compromised in this disorder such as face perception and 'theory of mind'. Autistic people fail to activate the 'fusiform face area' during face perception tasks and show weak activation of medial frontal cortex and superior temporal gyrus when performing theory of mind tasks. These problems stem from a lack of integration of sensory processing with cognitive evaluation. I speculate that this problem reflects a failure of top-down modulation of early sensory processing. The problem could result from abnormal connectivity and lack of pruning.
Cortico-Brainstem Mechanisms of Biased Perceptual Decision-Making in the Context of Pain.
The journal of pain
Prior expectations can bias how we perceive pain. Using a drift diffusion model, we recently showed that this influence is primarily based on changes in perceptual decision-making (indexed as shift in starting point). Only during unexpected application of high-intensity noxious stimuli, altered information processing (indexed as increase in drift rate) explained the expectancy effect on pain processing. Here, we employed functional magnetic resonance imaging to investigate the neural basis of both these processes in healthy volunteers. On each trial, visual cues induced the expectation of high- or low-intensity noxious stimulation or signaled equal probability for both intensities. Participants categorized a subsequently applied electrical stimulus as either low- or high-intensity pain. A shift in starting point towards high pain correlated negatively with right dorsolateral prefrontal cortex activity during cue presentation underscoring its proposed role of "keeping pain out of mind". This anticipatory right dorsolateral prefrontal cortex signal increase was positively correlated with periaqueductal gray (PAG) activity when the expected high-intensity stimulation was applied. A drift rate increase during unexpected high-intensity pain was reflected in amygdala engagement and increased functional connectivity between amygdala and PAG. Our findings suggest involvement of the PAG in both decision-making bias and altered information processing to implement expectancy effects on pain. PERSPECTIVE: Modulation of pain through expectations has been linked to changes in perceptual decision-making and altered processing of afferent information. Our results suggest involvement of the dorsolateral prefrontal cortex, amygdala, and periaqueductal gray in these processes.
The computational origin of representation.
Piantadosi Steven T
Minds and machines
Each of our theories of mental representation provides some insight into how the mind works. However, these insights often seem incompatible, as the debates between symbolic, dynamical, emergentist, sub-symbolic, and grounded approaches to cognition attest. Mental representations-whatever they are-must share many features with each of our theories of representation, and yet there are few hypotheses about how a synthesis could be possible. Here, I develop a theory of the underpinnings of symbolic cognition that shows how sub-symbolic dynamics may give rise to higher-level cognitive representations of structures, systems of knowledge, and algorithmic processes. This theory implements a version of conceptual role semantics by positing an internal universal representation language in which learners may create mental models to capture dynamics they observe in the world. The theory formalizes one account of how truly novel conceptual content may arise, allowing us to explain how even elementary logical and computational operations may be learned from a more primitive basis. I provide an implementation that learns to represent a variety of structures, including logic, number, kinship trees, regular languages, context-free languages, domains of theories like magnetism, dominance hierarchies, list structures, quantification, and computational primitives like repetition, reversal, and recursion. This account is based on simple discrete dynamical processes that could be implemented in a variety of different physical or biological systems. In particular, I describe how the required dynamics can be directly implemented in a connectionist framework. The resulting theory provides an "assembly language" for cognition, where high-level theories of symbolic computation can be implemented in simple dynamics that themselves could be encoded in biologically plausible systems.
Capturing the objects of vision with neural networks.
Peters Benjamin,Kriegeskorte Nikolaus
Nature human behaviour
Human visual perception carves a scene at its physical joints, decomposing the world into objects, which are selectively attended, tracked and predicted as we engage our surroundings. Object representations emancipate perception from the sensory input, enabling us to keep in mind that which is out of sight and to use perceptual content as a basis for action and symbolic cognition. Human behavioural studies have documented how object representations emerge through grouping, amodal completion, proto-objects and object files. By contrast, deep neural network models of visual object recognition remain largely tethered to sensory input, despite achieving human-level performance at labelling objects. Here, we review related work in both fields and examine how these fields can help each other. The cognitive literature provides a starting point for the development of new experimental tasks that reveal mechanisms of human object perception and serve as benchmarks driving the development of deep neural network models that will put the object into object recognition.
From Micro to Macro: The Combination of Consciousness.
Frontiers in psychology
Crick and Koch's 1990 "neurobiological theory of consciousness" sparked the race for the physical correlates of subjective experience. 30 years later, cognitive sciences trend toward consideration of the brain's electromagnetic field as the primary seat of consciousness, the "to be" of the individual. Recent advancements in laboratory tools have preceded an influx of studies reporting a synchronization between the neuronally generated EM fields of interacting individuals. An embodied and enactive neuroscientific approach has gained traction in the wake of these findings wherein consciousness and cognition are theorized to be regulated and distributed beyond the individual. We approach this frontier to extend the implications of person-to-person synchrony to propose a process of combination whereby coupled individual agents merge into a hierarchical cognitive system to which they are subsidiary. Such is to say, the complex mammalian consciousness humans possess may not be the tip of the iceberg, but another step in a succeeding staircase. To this end, the axioms and conjectures of General Resonance Theory are utilized to describe this phenomenon of interpersonal resonant combination. Our proposal describes a coupled system of spatially distributed EM fields that are synchronized through recurrent, entraining behavioral interactions. The system, having achieved sufficient synchronization, enjoys an optimization of information flow that alters the conscious states of its merging agents and enhances group performance capabilities. In the race for the neurobiological correlates of subjective experience, we attempt the first steps in the journey toward defining the physical basis of "group consciousness." The establishment of a concrete account of the combination of consciousness at a scale superseding individual human consciousness remains speculation, but our suggested approach provides a framework for empirical testing of these possibilities.
Consciousness as a concrete physical phenomenon.
Jylkkä Jussi,Railo Henry
Consciousness and cognition
The typical empirical approach to studying consciousness holds that we can only observe the neural correlates of experiences, not the experiences themselves. In this paper we argue, in contrast, that experiences are concrete physical phenomena that can causally interact with other phenomena, including observers. Hence, experiences can be observed and scientifically modelled. We propose that the epistemic gap between an experience and a scientific model of its neural mechanisms stems from the fact that the model is merely a theoretical construct based on observations, and distinct from the concrete phenomenon it models, namely the experience itself. In this sense, there is a gap between any natural phenomenon and its scientific model. On this approach, a neuroscientific theory of the constitutive mechanisms of an experience is literally a model of the subjective experience itself. We argue that this metatheoretical framework provides a solid basis for the empirical study of consciousness.
The Mechanical Basis of Memory - the MeshCODE Theory.
Goult Benjamin T
Frontiers in molecular neuroscience
One of the major unsolved mysteries of biological science concerns the question of where and in what form information is stored in the brain. I propose that memory is stored in the brain in a mechanically encoded binary format written into the conformations of proteins found in the cell-extracellular matrix (ECM) adhesions that organise each and every synapse. The MeshCODE framework outlined here represents a unifying theory of data storage in animals, providing read-write storage of both dynamic and persistent information in a binary format. Mechanosensitive proteins that contain force-dependent switches can store information persistently, which can be written or updated using small changes in mechanical force. These mechanosensitive proteins, such as talin, scaffold each synapse, creating a meshwork of switches that together form a code, the so-called MeshCODE. Large signalling complexes assemble on these scaffolds as a function of the switch patterns and these complexes would both stabilise the patterns and coordinate synaptic regulators to dynamically tune synaptic activity. Synaptic transmission and action potential spike trains would operate the cytoskeletal machinery to write and update the synaptic MeshCODEs, thereby propagating this coding throughout the organism. Based on established biophysical principles, such a mechanical basis for memory would provide a physical location for data storage in the brain, with the binary patterns, encoded in the information-storing mechanosensitive molecules in the synaptic scaffolds, and the complexes that form on them, representing the physical location of engrams. Furthermore, the conversion and storage of sensory and temporal inputs into a binary format would constitute an addressable read-write memory system, supporting the view of the mind as an organic supercomputer.
The physical basis of memory.
Gallistel C R
Neuroscientists are searching for the engram within the conceptual framework established by John Locke's theory of mind. This framework was elaborated before the development of information theory, before the development of information processing machines and the science of computation, before the discovery that molecules carry hereditary information, before the discovery of the codon code and the molecular machinery for editing the messages written in this code and translating it into transcription factors that mark abstract features of organic structure such as anterior and distal. The search for the engram needs to abandon Locke's conceptual framework and work within a framework informed by these developments. The engram is the medium by which information extracted from past experience is transmitted to the computations that inform future behavior. The information-conveying symbols in the engram are rapidly generated in the course of computations, which implies that they are molecules.