The wiring and rewiring of the brain never ends. Neural pathways are constantly being reshaped as we interact with the world and learn new things. At 91亚色 and MIT鈥檚 McGovern Institute, scientists are combining detailed analysis of brain activity with computational modelling to better understand that change.

91亚色 Assistant Professor , McGovern Institute Postdoctoral Fellow , an affiliate member of Kar鈥檚 lab and a member of the Centre for Integrative and Applied Neuroscience at 91亚色, and Investigator  worked together to compare what happened when monkeys and an artificial neural network with brain-like architecture were trained to visually identify the same objects. As the model鈥檚 performance improved, it reorganized itself in ways that closely paralleled changes the team detected in the brains of monkeys.

Their research, reported  , shows how changes in visual processing support animals鈥� ability to learn to discriminate new kinds of objects. By modelling these changes, the researchers hope to better predict how training reshapes perception, which could one day inform educational strategies for a wide range of learners.

鈥淥ur visual brain does not undergo a drastic reconfiguration when we learn a new object. Instead, it subtly reshapes how visual information is represented, making the distinctions that matter easier for the rest of the brain to read out. What is powerful about this study is that artificial neural networks could predict these subtle brain changes, giving us a concrete bridge between neuroscience and AI,鈥� says Kar. 鈥淏y translating inferences from animal neuroscience into computational models that can generate human-testable predictions, this framework makes translation much more feasible. It allows us to move from understanding how learning changes the macaque visual system to perhaps asking in the near future: why some children may struggle to form stable, generalizable representations 鈥� such as recognizing letters across fonts, linking words to objects, distinguishing faces, or applying knowledge in new situations.鈥�

Subtle changes

Learning about a new object calls on many parts of the brain. Visual-processing areas work together to make sense of information taken in through the eyes, then communicate with other brain areas to give the visual information meaning and guide behavior. Multiple parts of this system likely change during learning, and the research team wanted a clearer understanding of how that change is distributed.

Neuroscientists have debated how much change occurs in the brain鈥檚 visual-processing areas when an animal learns to recognize new objects. Some suspected that visual-processing pathways remain largely unchanged during learning to avoid broadly disrupting visual perception, but others have reported changes in activity within dedicated visual-processing areas with this kind of learning in humans and other primates. 

To take a closer look, the team focused on neural activity in a key component of the brain鈥檚 visual object-processing network, the inferior temporal (IT) cortex. By the time visual information reaches the IT cortex, key object features are clearly represented 鈥� so much so that it鈥檚 possible to 鈥渄ecode鈥� what object a monkey is seeing and even predict what errors it鈥檚 likely to make in identifying it, simply by analyzing patterns of neural activity there.

The team recorded neural activity in the IT cortex from two groups of monkeys as the animals looked at and identified images of objects. Some of the monkeys were untrained, so the images they saw had little meaning to them. Others had already learned to identify similar objects, so they could usually discriminate between elephants, chairs and other select objects, even when those objects were presented at different sizes, from different angles, or against different backgrounds than the ones they had seen before.

The broad pattern of activity in the IT cortex was largely similar in trained and untrained monkeys, suggesting that learning had not dramatically rewritten this high-level visual representation. Still, the group found subtle but reliable differences in the way neurons in the IT cortex responded to images in monkeys that had learned to recognize the kinds of objects they were shown, compared to the untrained monkeys.

Modelling learning

The group turned to computational models to investigate how those modest changes might contribute to learning. S枚rensen trained a suite of artificial neural networks whose internal components had been mapped to monkey IT cortex to identify the same categories of objects the monkeys had seen. The models were designed to learn using gradient descent, meaning they continually improved their accuracy by adjusting their parameters in response to errors.

Only some of the primate-like models showed learning behavior that matched that of the monkeys. In those that did, the IT-like stage changed in ways that resembled the learning-related changes the researchers had observed in the IT cortex of trained monkeys.

While gradient descent is commonly used to train artificial intelligence, it is generally considered biologically implausible as a direct model of how the brain learns. The researchers say the strong match in learning effects between the monkeys and their model demonstrates that these kinds of artificial neural networks can offer insights into biological learning at a useful level of abstraction, even if the brain does not learn in the same way.

鈥淭his shows that you can actually build in silico versions of future experiments,鈥� S枚rensen says. 鈥淚 think that gives us this playground of asking 鈥榳hat if鈥� questions 鈥� and potentially predicting new things that go beyond the experimenter鈥檚 intuition.鈥�

Most of the changes that allowed for learning in the model occurred outside of the IT cortex. 鈥淭his tells us that there is a lot between the area we recorded from and the final behavioral readout that needs to change during this process,鈥� Kar says. He adds that the team鈥檚 model will be useful as researchers look more deeply into how downstream brain areas contribute to learning.

The researchers stress that their study allowed more granular measurements of brain activity than would be possible in humans, and because monkeys鈥� brains are organized similarly to our own, their experiments have direct relevance to human learning. They say understanding the impact of plasticity in monkeys鈥� IT cortex could help researchers design new learning strategies for humans.

鈥淥ur prior conceptual working model of you 鈥� or a monkey 鈥� learning new objects was that your brain makes changes to synaptic connections that are largely downstream of your visual system, so you don鈥檛 destroy your visual system,鈥� says DiCarlo, who is also the Peter de Florez Professor of Brain and Cognitive Sciences and director of the MIT Siegel Family Quest for Intelligence. 鈥淵ou wouldn鈥檛 want your whole visual system to become an elephant detector [just because you鈥檝e learned to identify an elephant]. But this study went beyond that to say actually, when you learn 鈥榚lephant,鈥� your IT does change a little bit to make it a little more relevant to elephants.鈥�

That likely has consequences for recognizing other visual features, too. Subtle changes in the IT cortex that support elephant recognition might also make you better at identifying things other than elephants, DiCarlo says. Likewise, the same changes might make it a little harder to identify something else.

These kinds of consequences may be difficult to predict intuitively, but become obvious with computational modelling. For instance, the team鈥檚 models revealed that after learning to recognize new objects, the IT cortex contained more information about objects鈥� locations. By providing insights like these, models could aid the design of more effective training strategies for visual tasks, including for people with altered sensory processing, who may learn from visual information in atypical ways.

With files from MIT's McGovern Institute

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TORONTO, April 19, 2021 鈭� You feel like you鈥檙e floating or flying, or you have a hyper-awareness to light, smell and sound 鈭�听that perception of an altered state of consciousness is a result of increases in the brain鈥檚 signals and activity, according to a new study by 91亚色 psychology researchers.

鈥淲e have a hint that there could be brain modulations that induce someone to get into a trance state through training,鈥� says Psychology Professor Joseph DeSouza. 鈥淥ur results show how, when a person thinks they are in an altered state, their brain activity actually changes. No one has been able to show this in consciousness studies. This is our first step toward scanning what is happening in the brain during trance.鈥�

DeSouza, a member of 91亚色鈥檚 Centre for Vision Research, former postgraduate student Rebecca Rogerson, and postdoctoral researcher Rebecca Barnstaple,听conducted the study published in听.

During the study, the brain was scanned while the subject was in a trance state and the scan showed alterations in听 brain signals. The researchers found that regions in the brain were activated through music to induce this altered state of consciousness (ASC).

This is the first study to show heightened levels of brain activity in relation to perception of an altered state of consciousness 鈭� specifically trance 鈭� the researchers say. The findings may help shed light on how attention, volition, activation, and/or suppression of neural networks can play a role in consciousness.

In the research, researchers scanned the brain over eight minutes while the subject listened to five minutes听of trance-inducing music.听 The subject was observed to be in a trance state for two to five minutes and data from brain activation in both the auditory and orbitofrontal cortex were collected. Specific areas in the brain showed heightened modulations, including auditory (sound) and orbitofrontal. During the scan, the subject reported feeling physical sensations of tingling fingers, nausea, and a hyperawareness to light, odour, and sound normally associated with entering trance, saw themself flying or floating above an unknown locale and the subject also reported rapid fluttering of the eyelids, increased breathing, and an ecstatic feeling or sensation.

An altered state of consciousness can听change听how the听brain听works by diverting blood flow from the front of the听brain听to other areas.听Other common experiences that create听altered听states of听consciousness听are sleeping or daydreaming, sleep deprivation, euphoria or panic.听 Previous research has shown that meditation and hypnosis are other methods that can induce an altered state of consciousness and reduce stress and anxiety.

In some cultures, traditional healers are practitioners of ancient spiritual healing who commonly enter a trance state through fast rhythmic drumming techniques. During a trance state, the brain is able to supress external stimuli such as sounds. Despite the long history of trance by traditional healers, little is known about what happens in the brain and neural correlates.

DeSouza says that a task-specific brain network is created when these individuals train to become traditional healers, similar to those observed in听 professional musicians or dancers.

鈥淏rain plasticity is achieved through training the brain and now can be seen in our study during an altered state of consciousness.听 This is a one-subject case study and needs to be replicated by our group and others.鈥�

91亚色听is a modern, multi-campus, urban university located in Toronto, Ontario. Backed by a diverse group of students, faculty, staff, alumni and partners, we bring a uniquely global perspective to help solve societal challenges, drive positive change and prepare our students for success. 91亚色's fully bilingual Glendon Campus is home to Southern Ontario's Centre of Excellence for French Language and Bilingual Postsecondary Education. 91亚色鈥檚 campuses in Costa Rica and India offer students exceptional transnational learning opportunities and innovative programs. Together, we can make things right for our communities, our planet, and our future.听

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Media Contact:听

Anjum Nayyar, 91亚色 Media Relations, cell 437 242 1547,听anayyar@yorku.ca

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