Brain wiring is complex. The brain is a large, interconnected network of information processing cells known as neurons. How do 100 billion neurons make 100 trillion connections? Are there instructions for these connections written in the genome? If such a code exists, what is its logic? Work over the past century has uncovered what appears to be a code of proteins that serve as identification tags for neurons.
It all started with the invention of a new staining technique which allowed one of the fathers of neuroscience, Santiago Ramon y Cajal, to observe what had previously been unseeable — the complete structure of individual neurons. In 1890, while carefully drafting images by hand, Ramon y Cajal was struck by the behavior of growing axons – the cable like structure which starts at the neuron cell body and travels through many brain regions to send information. He noted that the axons were choosing where to grow “as if guided by an intelligent force”.
It would take nearly three quarters of a century before an experiment would be performed to test the intelligent force hypothesis. In a series of ingeniously designed experiments, Nobel Laureate Roger Sperry cut the optic nerve of frogs, twisted the eye in various directions, and asked: where will the regenerating fibres regrow? Will the axons return to their original target, now far from their original anatomical location, or will they follow their original path to a now improper target? What Sperry observed, time and again, was that axons traveled far from their original location to seek their original target – “regrowth always led to orderly functional recovery under conditions that precluded re-educative adjustments…It seemed a necessary conclusion…that the cells and fibres of the brain and cord must carry some kind of individual identification tags, presumably cytochemical in nature, by which they are distinguished…to the level of the single neuron”. Stated more simply, Sperry argued that each neuron seems to have a tag that contains not only information about self, but about its partner as well.
Patterns of connectivity
Despite these wonderful studies, the field was still not convinced. A decade after Sperry, another couple of neuroscientists, Alan Peters and Martin Feldman, used a clever technique to trace the path that neurons send their axons throughout the brain of the rat. While the tracing was crude compared to modern techniques, this novel method of observing natural processes provided interesting conclusions. Studying patterns of connectivity in the rat cerebral cortex, the scientists found no clear rules. No neurons seemed to be more connected to any other neurons more than expected by chance. They concluded that cortical connections were being made at random. Thus they proposed Peters’ rule: axons arrive at the correct region of the nervous system, and once they arrive connections are formed at random. No intelligent force is required for selective connections.
But how do neuronal projections arrive in the correct region in the first place? What is the logic by which neurons guide axons, over distances of up to one and a half metres in humans, to their final target? This question was solved in the 1990s following the identification of axon guidance cues. A system of guidance cues in three dimensions, which repel or attract growing axons, provide a system by which to pattern, with exquisite precision, the path of growing axons.
Thus, mechanisms for guidance have been solved. But what about connections? Is it true that the intelligent force of Ramon y Cajal controls guidance to location only but provides no clue for final connections? Do the chemical tags postulated by Sperry – Sperry molecules – exist? New evidence disproves Peters’ rule in many areas of the brain, reopening the search for an explanation of selective connections. If selective connections between neurons are required for maintaining important information processing tasks, we should expect them to be under strong evolutionary selection pressure.
Returning to Sperry’s conviction that molecules must guide connections, a recent study that screened for cell surface molecule interactions revealed a network of previously unknown molecular interactions. An astute group of neuroscientists expanded upon this interesting bit of chemistry, noting that many of the same molecules that had been found to be important in forming cellular connections showed differential expression patterns in subsets of neurons that make highly selective connections. Specifically, the interaction of two families of cell surface proteins form a combinatorial code through which the logic for selective connections can be encoded.
What then can we learn from this code? How can we apply our newfound knowledge of a combinatorial code that patterns specific neuronal connections to the benefit of mankind? The translational potential for improving human health is profound; far-reaching applications are apparent in diagnosis and treatment.
The diagnosis of most neuropsychiatric disorders relies on qualitative measures. While these are useful classifications with important therapeutic implications, our treatment could be better tailored to the disease process if we had a better understanding of the underlying pathophysiology.
Schizophrenia is common and devastating. It occurs in approximately one in 100 people with little difference across cultures. On the wards today, all cases of schizophrenia are treated with the same class of medication. Clinical experience, however, suggests one size does not fit all. One consistent feature is the generation of internal stimuli; patients hear voices, see visions, or feel a presence. Each of these symptoms suggest a disruption in the patient's neural architecture; circuits that should be receiving sensory input are instead receiving signals from improper internal neural sources. It is tempting to imagine the location of the miswiring: hearing voices involves improper connections in the auditory cortex; visions are aberrant input into the visual cortex; feeling a presence is due to altered computations in circuits which process information about balance and sensation. As circuit tracing techniques advance, these hypotheses will become testable.
As we deepen our understanding of the faulty circuit architecture that leads to schizophrenia, it is imperative that we profile the transcriptome of neurons in improperly formed circuits. If there is a disruption in neuron partner selection, understanding the differences in Sperry molecule expression between neurons involved in disease-causing circuits of patients versus those of healthy controls will be particularly important. Such an approach could be more generally applied to diseases of abnormal neural connectivity, such as autism spectrum disorders. Armed with accurate diagnoses, we could move forward with novel and rational therapies for neuropsychiatric disorders. If we can understand which circuits are improperly connected, we can start the difficult task of learning to rewire them.
For over 125 years we have been searching for the logic by which neurons form specific connections. By learning to read and write in the language of the newly found connectivity code, great strides will be made in our understanding and treatment of disease. The time is ripe to move forward and apply this knowledge to improve human health.
*Ben Cocanougher  is doing a PhD in Zoology. Picture credit: Neuronal activity c/o Wikimedia Commons.
- United States
- 2016 PhD Zoology
- St Catharine's College
I grew up catching praying mantises and damselflies in rural Kentucky. As an undergraduate at Centre College, I majored in Biochemistry and Molecular Biology; I spent my summers taking care of sick children at the Center for Courageous Kids and doing research in organic chemistry and neuroscience. I matriculated directly to the University of Rochester School of Medicine and Dentistry and completed my first three years of medical school. I then moved to Janelia Research Campus as a HHMI Medical Research Fellow; there I studied the neural and genetic bases of behavior. As a PhD student in Zoology, I will study adaptive behavior. All animals integrate information about past experience into future decisions; this is the basis of learning and memory. I am proposing to write a specific memory and read the memory trace in the brain. I will use the fruit fly as a model organism. By understanding mechanisms of memory storage, we can begin to investigate changes in memory formation in disease; this may allow us to develop rational therapies for disorders of memory formation, including autism and Alzheimer’s disease. After completing my PhD, I will return to finish my last year of medical school and pursue a career as a child neurologist and neuroscientist, using my lab to better understand the patients I see in clinic.