Oct 22, 2021 07:01 PM
https://aeon.co/essays/the-study-of-the-...erspective
EXCERPTS: . . . Basal cognition – the study of cognitive capacities in non-neural and simple neural organisms (to which my PhD research led) – is in its infancy as a field. However, evidence already shows that evolution had laid a solid foundation of capacities typically considered cognitive well before nervous systems appeared: about 500-650 million years ago. Perception, memory, valence, learning, decision-making, anticipation, communication – all once thought the preserve of humankind – are found in a wide variety of living things, including bacteria, unicellular eukaryotes, plants, fungi, non-neuronal animals, and animals with simple nervous systems and brains.
No amount of positive evidence for basal cognition will persuade a diehard neurocentric, however. (What do you mean by memory, valence, decision-making? Isn’t it a matter of definition?) Darwin’s radical idea must solve problems that cognitivism cannot...
[...] Cognitive neuroscience currently faces several challenges that must be overcome to understand how brains and nervous systems work, a prerequisite to understanding how cognitive capacities are generated by such systems. Three are sketched below. What seems needed in all three cases are simpler model systems, from which it’s more likely that fundamental discoveries about the drivers of organisms’ interactions with their surroundings will be made. Such discoveries might lead to general principles that can be tested in more complex organisms.
The first challenge to neuroscience relates to the ‘functional unit’ of the brain or nervous system. For more than a century, the single nerve cell has served as the structural and functional unit of brain activity. ... Each neuron was conceived as an on-off switch presumed capable of acting as a logic gate, enabling information to be ‘digitised’ (turned into ones or zeros) and thereby ‘encoded’.
Two findings have put pressure on this account. First is the number of different types of cells in the human brain. A recent study revealed no fewer than 75 different cell types: 24 excitatory types, 45 inhibitory types and six non-neuronal types. What they all do and how they interact are poorly understood. Second, it’s now clear that populations of neurons – acting in ensembles, networks and/or circuits – are the most likely units of functional activity. Defining a neural ensemble, network and/or circuit is non-trivial, however; so is understanding how they form and interact, how stable they are over time, how and whether they’re nested in hierarchies, and how they generate behaviour. All are still major works in progress.
[...] The second challenge to neuroscience arrived when a heroic scientific success disclosed a ‘surprising failure’. The wiring diagram of the C elegans brain, a project started in cognitivism’s heyday, was completed. Connections between the worm’s 302 neurons were mapped, and behaviours associated with most cell types defined. Yet this stunning achievement revealed little about how and why a worm behaves the way it does – the aim of the research. According to the neuroscientist Cori Bargmann, C elegans studies ‘suggest that it will not be possible to read a [neural] wiring diagram as if it were a set of instructions’ for behaviour. This is for two main reasons.
First, behaviour under more ecologically realistic conditions violated key assumptions about the causal relation between activity in particular neurons (eg, sensory, motor, integrative) and certain behaviours (forward and reverse locomotion, feeding) derived from genetic knock-out studies. On the contrary, a single behaviour might be induced by several different neural circuits. Moreover, one circuit’s starting point might result in different – even opposing – behaviours in different circumstances. In short, a single wiring diagram represented more potential behaviour than originally assumed.
Second, context and the organism’s internal state proved much more important to behaviour than initially thought. Context and internal state are believed to be signalled by molecules – neuromodulators and their smaller cousins, neuropeptides – although precisely how is unclear. These signalling molecules, many of which are produced by neurons themselves, can alter neural function from seconds to minutes to hours; interact with different targets (other neurons, muscle cells, glands); and activate or silence entire circuits. C elegans produces more than 100 such molecules.
In bacteria and unicellular eukaryotes (cells with a defined nucleus, which bacteria lack), coordinated activity involving thousands of individuals – the equivalent of multicellular behaviour – is also facilitated by signalling molecules, a phenomenon called quorum sensing. Quorum sensing molecules have been compared to hormones because they alter behaviour by similar mechanisms...
[...] The third challenge to neuroscience wasn’t a paradigm misfire; it came from left-field. Cognitive processes were traditionally conceived as entirely reactive: something in the world affects the organism (input), resulting in a response (output). The input-output view is basic to cognitivism. Discovery in the late 1990s of spontaneous, ongoing brain activity without an external stimulus thus was initially thought to be an artefact of imaging technology, then deeply puzzling, and now is a major research field. The default mode network is defined as functionally connected brain regions that are active during wakeful rest and inactive during task-oriented behaviour. Chimpanzees and mice exhibit default mode activity. In humans, default network disturbance is associated with psychiatric disorders. This means it’s important to cognitive functioning.
The default mode network is not the only spontaneous oscillation in the brain, far from it. The neuroscientist György Buzsáki, who has worked hard to draw attention to the ‘rhythms of the brain’, claims that this kind of brain activity is not system noise but ‘is actually the source of our cognitive abilities’ and might be the brain’s ‘fundamental organiser of neuronal information’...
Oscillations are produced by ion channels in cellular membranes found across the tree of life. Michael Levin’s lab has shown that ion channel-generated bioelectricity plays a key role in ‘pattern memory’ for regenerating animal bodies. Headless planaria regenerate brains, tadpoles regrow tails, adult frogs regrow functional hindlimbs (if induced), and electrical stimulation can make things grow where they shouldn’t – for example, a second worm head where a tail should be. For Levin, pragmatic acceptance that even cells in tissues inherit some of the decision-making capacities of their unicellular forebears – what he calls ‘the cognitive lens’ – could transform fields as different as developmental biology, immunology, neuroscience, bioengineering and artificial intelligence.
What is needed is a shift in perspective. In The Brain from Inside Out (2019), György Buzsáki argues that many of the seemingly intractable problems that neuroscience faces arise entirely from ‘human-constructed ideas’ about how the mind/brain must work, based on philosophical and scientific conjecture over millennia, which are then shoe-horned on to observed brain activity. This is what he calls the ‘outside-in’ perspective: ‘the dominant framework of mainstream neuroscience, which suggests that the brain’s task is to perceive and represent the world, process information, and decide how to respond … in an “outside-in” manner’. This is what Maturana calls ‘observer dependence’, from the observer’s point of view, not the observed system’s. The spontaneously active brain has its own logic, of which almost nothing is understood. Deciphering this logic from the perspective of the system generating the activity – from ‘inside-out’ – should be the primary goal of neuroscience, Buzsáki argues, not mapping human assumptions on to neuronal observations.
I made a similar distinction 15 years ago. I called the view of cognition grounded in ideas originating in human experience and reflection the anthropogenic (human-born) approach, what Buzsáki calls ‘outside-in’. Although cognitivism asserts that cognition can be realised in different physical forms (including robots), the approach remains anthropogenic because it derives from the human capacity to compute numbers. The contrast case is what I call the biogenic (life-born) approach, which privileges the biological mode of existence as the source of cognition and entails the ‘inside-out’ view.
If understanding human cognition is the goal, then a biogenic/inside-out approach is the most promising path to take us beyond this geriatric shuffle on a road to nowhere. Given the massive investment of public and private funds, to say nothing of human ingenuity, time and effort over the past 70 years, we should by now know so much more about what cognition is, what it’s for, and how it works – theories of these things, not simply data derived from brain activity. Think of how society has transformed since the 1950s. How many dogmas have crashed and burned? How much has been learned in so many fields? (MORE - missing details)
EXCERPTS: . . . Basal cognition – the study of cognitive capacities in non-neural and simple neural organisms (to which my PhD research led) – is in its infancy as a field. However, evidence already shows that evolution had laid a solid foundation of capacities typically considered cognitive well before nervous systems appeared: about 500-650 million years ago. Perception, memory, valence, learning, decision-making, anticipation, communication – all once thought the preserve of humankind – are found in a wide variety of living things, including bacteria, unicellular eukaryotes, plants, fungi, non-neuronal animals, and animals with simple nervous systems and brains.
No amount of positive evidence for basal cognition will persuade a diehard neurocentric, however. (What do you mean by memory, valence, decision-making? Isn’t it a matter of definition?) Darwin’s radical idea must solve problems that cognitivism cannot...
[...] Cognitive neuroscience currently faces several challenges that must be overcome to understand how brains and nervous systems work, a prerequisite to understanding how cognitive capacities are generated by such systems. Three are sketched below. What seems needed in all three cases are simpler model systems, from which it’s more likely that fundamental discoveries about the drivers of organisms’ interactions with their surroundings will be made. Such discoveries might lead to general principles that can be tested in more complex organisms.
The first challenge to neuroscience relates to the ‘functional unit’ of the brain or nervous system. For more than a century, the single nerve cell has served as the structural and functional unit of brain activity. ... Each neuron was conceived as an on-off switch presumed capable of acting as a logic gate, enabling information to be ‘digitised’ (turned into ones or zeros) and thereby ‘encoded’.
Two findings have put pressure on this account. First is the number of different types of cells in the human brain. A recent study revealed no fewer than 75 different cell types: 24 excitatory types, 45 inhibitory types and six non-neuronal types. What they all do and how they interact are poorly understood. Second, it’s now clear that populations of neurons – acting in ensembles, networks and/or circuits – are the most likely units of functional activity. Defining a neural ensemble, network and/or circuit is non-trivial, however; so is understanding how they form and interact, how stable they are over time, how and whether they’re nested in hierarchies, and how they generate behaviour. All are still major works in progress.
[...] The second challenge to neuroscience arrived when a heroic scientific success disclosed a ‘surprising failure’. The wiring diagram of the C elegans brain, a project started in cognitivism’s heyday, was completed. Connections between the worm’s 302 neurons were mapped, and behaviours associated with most cell types defined. Yet this stunning achievement revealed little about how and why a worm behaves the way it does – the aim of the research. According to the neuroscientist Cori Bargmann, C elegans studies ‘suggest that it will not be possible to read a [neural] wiring diagram as if it were a set of instructions’ for behaviour. This is for two main reasons.
First, behaviour under more ecologically realistic conditions violated key assumptions about the causal relation between activity in particular neurons (eg, sensory, motor, integrative) and certain behaviours (forward and reverse locomotion, feeding) derived from genetic knock-out studies. On the contrary, a single behaviour might be induced by several different neural circuits. Moreover, one circuit’s starting point might result in different – even opposing – behaviours in different circumstances. In short, a single wiring diagram represented more potential behaviour than originally assumed.
Second, context and the organism’s internal state proved much more important to behaviour than initially thought. Context and internal state are believed to be signalled by molecules – neuromodulators and their smaller cousins, neuropeptides – although precisely how is unclear. These signalling molecules, many of which are produced by neurons themselves, can alter neural function from seconds to minutes to hours; interact with different targets (other neurons, muscle cells, glands); and activate or silence entire circuits. C elegans produces more than 100 such molecules.
In bacteria and unicellular eukaryotes (cells with a defined nucleus, which bacteria lack), coordinated activity involving thousands of individuals – the equivalent of multicellular behaviour – is also facilitated by signalling molecules, a phenomenon called quorum sensing. Quorum sensing molecules have been compared to hormones because they alter behaviour by similar mechanisms...
[...] The third challenge to neuroscience wasn’t a paradigm misfire; it came from left-field. Cognitive processes were traditionally conceived as entirely reactive: something in the world affects the organism (input), resulting in a response (output). The input-output view is basic to cognitivism. Discovery in the late 1990s of spontaneous, ongoing brain activity without an external stimulus thus was initially thought to be an artefact of imaging technology, then deeply puzzling, and now is a major research field. The default mode network is defined as functionally connected brain regions that are active during wakeful rest and inactive during task-oriented behaviour. Chimpanzees and mice exhibit default mode activity. In humans, default network disturbance is associated with psychiatric disorders. This means it’s important to cognitive functioning.
The default mode network is not the only spontaneous oscillation in the brain, far from it. The neuroscientist György Buzsáki, who has worked hard to draw attention to the ‘rhythms of the brain’, claims that this kind of brain activity is not system noise but ‘is actually the source of our cognitive abilities’ and might be the brain’s ‘fundamental organiser of neuronal information’...
Oscillations are produced by ion channels in cellular membranes found across the tree of life. Michael Levin’s lab has shown that ion channel-generated bioelectricity plays a key role in ‘pattern memory’ for regenerating animal bodies. Headless planaria regenerate brains, tadpoles regrow tails, adult frogs regrow functional hindlimbs (if induced), and electrical stimulation can make things grow where they shouldn’t – for example, a second worm head where a tail should be. For Levin, pragmatic acceptance that even cells in tissues inherit some of the decision-making capacities of their unicellular forebears – what he calls ‘the cognitive lens’ – could transform fields as different as developmental biology, immunology, neuroscience, bioengineering and artificial intelligence.
What is needed is a shift in perspective. In The Brain from Inside Out (2019), György Buzsáki argues that many of the seemingly intractable problems that neuroscience faces arise entirely from ‘human-constructed ideas’ about how the mind/brain must work, based on philosophical and scientific conjecture over millennia, which are then shoe-horned on to observed brain activity. This is what he calls the ‘outside-in’ perspective: ‘the dominant framework of mainstream neuroscience, which suggests that the brain’s task is to perceive and represent the world, process information, and decide how to respond … in an “outside-in” manner’. This is what Maturana calls ‘observer dependence’, from the observer’s point of view, not the observed system’s. The spontaneously active brain has its own logic, of which almost nothing is understood. Deciphering this logic from the perspective of the system generating the activity – from ‘inside-out’ – should be the primary goal of neuroscience, Buzsáki argues, not mapping human assumptions on to neuronal observations.
I made a similar distinction 15 years ago. I called the view of cognition grounded in ideas originating in human experience and reflection the anthropogenic (human-born) approach, what Buzsáki calls ‘outside-in’. Although cognitivism asserts that cognition can be realised in different physical forms (including robots), the approach remains anthropogenic because it derives from the human capacity to compute numbers. The contrast case is what I call the biogenic (life-born) approach, which privileges the biological mode of existence as the source of cognition and entails the ‘inside-out’ view.
If understanding human cognition is the goal, then a biogenic/inside-out approach is the most promising path to take us beyond this geriatric shuffle on a road to nowhere. Given the massive investment of public and private funds, to say nothing of human ingenuity, time and effort over the past 70 years, we should by now know so much more about what cognition is, what it’s for, and how it works – theories of these things, not simply data derived from brain activity. Think of how society has transformed since the 1950s. How many dogmas have crashed and burned? How much has been learned in so many fields? (MORE - missing details)